Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
CLAIM INTERPRETATION
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following claim limitations have been interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because it they use a generic placeholder “unit” coupled with functional language and without reciting sufficient structure to achieve the function. Furthermore, the generic placeholder is not preceded by a structural modifier:
Claim 1, 15 and 17 (dependent claims 2-14 and 16):
a determination unit configured to determine whether or not a medical image is an image that is difficult to make a judgement about regarding a radiological interpretation item;
a search unit configured to search for a similar medical image that is similar to the medical image; and
a display control unit configured to display the similar medical image on a display unit based on a result of the determination.
If Applicant asserts that the claim element “unit” is a limitation that does not invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, 6th paragraph. If applicant does not wish to have the claim limitation treated under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, 6th Paragraph applicant may:
(a) Amend the claim to add structure, material or acts that are sufficient to perform the claimed function; or
(b) Present a sufficient showing that the claim limitation recites sufficient structure, material, or acts for performing the claimed function to preclude application of 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. For more information, see MPEP § 2181.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The limitations, under their broadest reasonable interpretation, cover mental process using collected image data based on the visualization and matching of the search medical image data (concept performed in a human mind, including as observation, evaluation, judgment, prediction, etc.). This judicial exception is not integrated into a practical application because the steps do not add meaningful limitations to be considered specifically applied to a particular technological problem to be solved. The claims 1-20 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the steps of the claimed invention can be done mentally and no additional features in the claims would preclude them from being performed as such except for the generic computer elements and generic display recited as high level of generality (i.e., processor and generic display)
According to the USPTO guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that claims 1, 5 and 6 are directed to an abstract idea as shown below:
Regarding independent claims 1, 15, 17, 18 and 19.
STEP 1: Do the claims fall within one of the statutory categories?
YES.
Claims 1, 15, 17, 18 and 19 are directed to an apparatus and a method which satisfy system and process.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?
YES.
The claims are directed toward a mental process (i.e. abstract idea).
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
Claims 1, 15, 17, 18 and 19 comprise a mental process that can be practicably performed in the human mind using paper pencil (or generic computers or components and generic display configured to perform the process) and, therefore, an abstract idea.
Regarding Claim(s) 1, 15, 17, 18 and 19: (representative claim 1)
An information processing apparatus comprising:
a determination unit configured to determine whether or not a medical image is an image that is difficult to make a judgement about regarding a radiological interpretation item (medical technician inspecting the collected medical image data and mentally making judgement/prediction if the collected image is difficult to interpretate and understand i.e. mental process);
a search unit configured to search for a similar medical image that is similar to the medical image and whose radiological interpretation item has a high degree of reliability, when the medical image is determined as an image that is difficult to make a judgement about (medical technician searching similar medical images in the collection of medical images stored in the drawer of technician desk whose interpretation are higher quality based on doctor confirmation i.e., mental process of searching the previously acquired higher quality/reliable images confirm by doctor/expert) ; and
a display control unit configured to display the similar medical image on a display unit (medical technician display the hard copy of the most similar image based on matching/comparing i.e., mental process. Furthermore display control unit is insignificant post solution active).
The above limitations, as drafted, is a simple process that, under their broadest reasonable interpretation, covers performance of the limitations in the mind by a person/technician using human intelligence. Furthermore limitations “a determination unit configured to determine whether or not a medical image is an image that is difficult to make a judgement about regarding a radiological interpretation item (medical technician inspecting the collected medical image data and mentally making judgement/prediction if the collected image is difficult to interpretate and understand i.e. mental process), a search unit configured to search for a similar medical image that is similar to the medical image and whose radiological interpretation item has a high degree of reliability, when the medical image is determined as an image that is difficult to make a judgement about (medical technician searching similar medical images in the collection of medical images stored in the drawer of technician desk whose interpretation are higher quality based on doctor confirmation i.e., mental process of searching the previously acquired higher quality/reliable images confirm by doctor/expert) and a display control unit configured to display the similar medical image on a display unit (medical technician display the hard copy of the most similar image based on matching/comparing i.e., mental process. Furthermore display control unit is insignificant post solution active)” are insignificant.
The Examiner notes that under MPEP 2106.04(A) (2) (III), the courts consider a mental process (thinking, human intelligence) that can be performed in the mind/intelligence using a paper and pencil to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[Mental processes and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978).
Other than generic and conventional computing unit/hardware and generic and conventional display unit recited in the independent claims 1, 15 and 17 and disclosed in the specification, nothing in the independent claims elements preclude the processing from being performed as mental process, or merely based on the observations, evaluation, judgement, thought process using based on the human intelligence and mental process. The generic and conventional computing unit and generic display unit recited in independent claims 1, 15 and 17 is a mere idea of a solution without details per MPEP 2106.05( f ) or the idea of a technological environment without detail per MPEP 2106.05 ( h ). The generic computing unit and generic display unit are recited as just to automate the mental process. Furthermore the display control unit is insignificant post solution activity without any detail (Step 2A, prong 1 Test Abstract idea = Yes).
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
[YES/NO].
The claims do not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to affect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
Claim(s) 1, 15, 17 and 19 do not recite any of the exemplary considerations that are indicative of an abstract idea having been integrated into a practical application. Claim(s) 1, 15, 17, and 19 recite(s) the further limitations of: “a determination unit configured to determine whether or not a medical image is an image that is difficult to make a judgement about regarding a radiological interpretation item (medical technician inspecting the collected medical image data and mentally making judgement/prediction if the collected image is difficult to interpretate and understand i.e. mental process), a search unit configured to search for a similar medical image that is similar to the medical image and whose radiological interpretation item has a high degree of reliability, when the medical image is determined as an image that is difficult to make a judgement about (medical technician searching similar medical images in the collection of medical images stored in the drawer of technician desk whose interpretation are higher quality based on doctor confirmation i.e., mental process of searching the previously acquired higher quality/reliable images confirm by doctor/expert) and a display control unit configured to display the similar medical image on a display unit (medical technician display the hard copy of the most similar image based on matching/comparing i.e., mental process. Furthermore display control unit is insignificant post solution active)”.
The above limitations are recited at a high level of generality (i.e. as a general action of mental process based on acquiring step) and amounts to mere post solution actions, which is a form of insignificant extra-solution activity without further detail. Furthermore, the claims are claimed generically and are operating in their ordinary capacity such that they do not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
Other than generic and conventional computing unit/hardware and generic and conventional display unit recited in the independent claims 1, 15 and 17 and disclosed in the specification, nothing in the independent claim(s) elements preclude the processing from being performed as mental process, or merely based on the observations, evaluation, judgement, thought process using based on the human intelligence and mental process. The generic and conventional computing unit and generic display unit recited in independent claims 1, 15 and 17 is a mere idea of a solution without details per MPEP 2106.05( f ) or the idea of a technological environment without detail per MPEP 2106.05 ( h ). The generic computing unit and generic display unit are recited as just to automate the mental process. Furthermore the display control unit is insignificant post solution activity without any detail (Step 2A, prong 2 Test Abstract idea = Yes).
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
NO.
The claims do not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
Other than generic and conventional computing unit/hardware and generic and conventional display unit recited in the independent claims 1, 15 and 17 and disclosed in the specification, nothing in the independent claim (s) elements preclude the processing from being performed as mental process, or merely based on the observations, evaluation, judgement, thought process using based on the human intelligence and mental process. The generic and conventional computing unit and generic display unit recited in independent claims 1, 15 and 17 is a mere idea of a solution without details per MPEP 2106.05( f ) or the idea of a technological environment without detail per MPEP 2106.05 ( h ). The generic computing unit and generic display unit are recited as just to automate the mental process. Furthermore the display control unit is insignificant post solution activity without any detail
Thus, since Claim(s) 1, 15, 17, 18 and 19 are: (a) directed toward an abstract idea, (b) do not recite additional elements that integrate the judicial exception into a practical application, and (c) do not recite additional elements that amount to significantly more than the judicial exception, it is clear that Claim(s) 1, 15, 17, 18 and 19 are not eligible subject matter under 35 U.S.C 101 (Step 2B, Test Abstract idea = Yes).
Regarding dependent claims 2-14, 16 and 20, claims 2-14, 16 and 20 further limit the abstract idea of performance of the limitations in the mind based on mental process of observations, judgement, evaluation, and thought process. Other than generic and conventional computing unit/hardware, conventional imaging devices and generic and conventional display unit recited in the independent claims 1, 15 and 17 and disclosed in the specification, nothing in the independent claim (s) elements preclude the processing from being performed as mental process, or merely based on the observations, evaluation, judgement, thought process using based on the human intelligence and mental process. The generic and conventional computing unit and generic display unit recited in independent claims 1, 15 and 17 is a mere idea of a solution without details per MPEP 2106.05( f ) or the idea of a technological environment without detail per MPEP 2106.05 ( h ). The generic computing unit and generic display unit are recited as just to automate the mental process. Furthermore the display control unit is insignificant post solution activity without any detail. There are no additional elements in the claims that would integrate the abstract idea into a practical application. The claims do not mention any improvement to a computer or to any other technology or technical field. The limitations of claims 2-14, 16 and 20 fail to add inventive concept to otherwise mental process. Therefore the dependent claims 2-14, 16 and 20 are no more than abstract idea without significantly more.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Miyasa et al. (US 20110099032, USPTO-892) in view of Miyasa et al. (JP 2014039852-USPTO-892)
Regarding claim 1, 15, 17-18 and 20 Miyasa (US 20110099032) disclose information processing apparatus/method (Miyasa Fig. 1-2, paragraph 0049) comprising:
a determination unit configured to determine whether or not a medical image is an image that is difficult to make a judgement about regarding a radiological interpretation item (Myasa Fig. 1 and Fig. 2, blocks S105-S106, Fig.3 block, paragraph 0047 states "diagnostic difficulty level" of a medical case relating to a medical image similar to a diagnostic target medical image corresponds to a "diagnostic difficulty level" of the diagnostic target medical image. It is presumed that the necessity of presenting the similar case is variable depending on the "diagnostic difficulty level" and paragraph 0050 disclose information processing apparatus 100-1 performs processing for medical case data including examination information of various subjects (patients). The case database 210 is a medical case data storage unit configured to store medical case data, which include examination information of subjects in association with medical practice difficulty level information based on the examination information. More specifically, the case database 210 stores medical case data relating to medical practice completed (e.g., diagnosis completed and treatment completed) medical cases. This obviously corresponds to a determination unit configured to determine whether or not a medical image is an image that is difficult to make a judgement about regarding a radiological interpretation item);
a search unit configured to search for a similar medical image that is similar to the medical image and when the medical image is determined as an image that is difficult to make a judgement about (Miyasa Fig. 1 blocks 104, 210 and 105-106 and 230 paragraph 0060 display recommendation level calculation unit 105 is functionally configured to calculate a display recommendation level of the similar case data based on a medical practice difficulty level of the similar case data searched by the similar case search unit 104 (i.e., the diagnostic difficulty level in the present exemplary embodiment and paragraph 0061 disclose The medical reference information search unit 106 is functionally configured to search medical reference information, such as disease information, from the medical information database 230. The storage unit 107 stores various types of information acquired by the medical image acquisition unit 101, the feature information extraction unit 102, the previous image acquisition unit 103, the similar case search unit 104, the display recommendation level calculation unit 105, and the medical reference information search unit 106. This obviously corresponds to a search unit configured to search for a similar medical image that is similar to the medical image and when the medical image is determined as an image that is difficult to make a judgement about ); and
a display control unit configured to display the similar medical image on a display unit (Miyasa Fig. 1 blocks 108-109 paragraph 0063 disclose the display mode determination unit 108 determines a display mode applicable to the similar case data referring to a display recommendation level calculated by the display recommendation level calculation unit 105 based on the medical practice difficulty level (i.e., the diagnostic difficulty level in the present exemplary embodiment and paragraph 0064 disclose The display unit 109 is functionally configured to display similar case data according to the display mode determined by the display mode determination unit 108. This obviously corresponds to a display control unit configured to display the similar medical image on a display unit ).
Miyasa (US 20110099032) has not explicitly disclose a search unit configured to search for a similar medical image that is similar to the medical image and whose radiological interpretation item has a high degree of reliability, when the medical image is determined as an image that is difficult to make a judgement about
In the same field of endeavor Miyasa (JP 2014039852) disclose a search unit configured to search for a similar medical image that is similar to the medical image based on the difficulty (Abstract, page 5 <Step> 7th paragraph thru 8th paragraph discloses in step S103, the similar case search unit 104 first acquires the image feature amount of the diagnosis target image stored in the storage unit 107 in step S102. Next, the similar case search unit 104 performs similar case search processing for extracting case data having image feature amounts similar to the image feature amounts of the acquired diagnosis target image from the case database 210 (similar case search step) and As shown in FIG. 3, the case data stored in the case database 210 of the present embodiment includes identification information 310, clinical information 320, image information 330, diagnosis information 340, and diagnosis difficulty level information 350. It is. Specifically, the case data of this embodiment includes, for example, examination information of a subject including identification information 310, clinical information 320, image information 330, and diagnostic information 340, and diagnostic difficulty information 350 indicating the difficulty of medical practice. Are stored in association with each other. All this obviously corresponds to a search unit configured to search for a similar medical image that is similar to the medical image based on the difficulty)
a search unit configured to search for a similar medical image that is similar to the medical image and whose radiological interpretation item has a high degree of reliability, when the medical image is determined as an image that is difficult to make a judgement about (Miyasa, page 15, {second Embodiment}, lines 2-15 Miyasa disclose
In the information processing apparatus 100-1 according to the first embodiment described above, the display recommendation degree P of the similar case is calculated based on the diagnosis difficulty level in the similar case. On the other hand, in the information processing apparatus 100-2 according to the second embodiment, the similarity is based on both the diagnosis difficulty level in a similar case and the disease determination difficulty level obtained by image analysis of the diagnosis target image. The case is different from the first embodiment in that the case recommendation degree P is calculated. Here, the “disease discrimination difficulty level” represents the degree of difficulty of disease discrimination performed by image analysis of the diagnosis target image. Thereby, even when the similarity of the similar case with respect to the diagnosis target image is low, that is, the reference degree of the similar case is low, the reliability of the display recommendation degree P is increased by increasing the weight of the disease determination difficult level, which is another index. Deterioration can be prevented. This obviously corresponds to a search unit configured to search for a similar medical image that is similar to the medical image and whose radiological interpretation item has a high degree of reliability, when the medical image is determined as an image that is difficult to make a judgement about) and
display control unit to display similar image (Miyasa, page 15, {second Embodiment}, lines 2-15 Miyasa disclose In the information processing apparatus 100-1 according to the first embodiment described above, the display recommendation degree P of the similar case is calculated based on the diagnosis difficulty level in the similar case. On the other hand, in the information processing apparatus 100-2 according to the second embodiment, the similarity is based on both the diagnosis difficulty level in a similar case and the disease determination difficulty level obtained by image analysis of the diagnosis target image. The case is different from the first embodiment in that the case recommendation degree P is calculated. Here, the “disease discrimination difficulty level” represents the degree of difficulty of disease discrimination performed by image analysis of the diagnosis target image. Thereby, even when the similarity of the similar case with respect to the diagnosis target image is low, that is, the reference degree of the similar case is low, the reliability of the display recommendation degree P is increased by increasing the weight of the disease determination difficulty level, which is another index. Deterioration can be prevented)
Therefore it would be obvious before the filing data of the claimed invention to use teaching of Miyasa (US Patent) in the system of Miyasa (JP Patent) to search for a similar medical image that is similar to the medical image and whose radiological interpretation item has a high degree of reliability, when the medical image is determined as an image that is difficult to make a judgement about because such a system/process provide automated system/process to search for similar radiological images whose radiological interpretation item has a higher quality of interpretation.
Regarding claim 2 Miyasa (US 20110099032) disclose the display control unit displays, on the display unit, the medical image and identification information regarding the radiological interpretation item attached to the similar medical image, together with the similar medical image (Miyasa paragraph 0074, As illustrated in FIG. 3, the medical case data stored in the case database 210 according to the present exemplary embodiment includes identification information 310, clinical information 320, image information 330, diagnostic information 340, and diagnostic difficulty level information 350 paragraph 0075 More specifically, the medical case data according to the present exemplary embodiment includes examination information of a subject, which is, for example, composed of the identification information 310, the clinical information 320, the image information 330, and the diagnostic information 340. The examination information of each subject is stored in association with the diagnostic difficulty level information 350 that represents a medical practice difficulty level and paragraph 0084 the similar case search unit 104 transmits the k pieces of similar case data acquired by the similar case search processing to the display recommendation level calculation unit 105 and the storage unit 107).
Regarding claim 3 Miyasa (US 20110099032) disclose a specifying unit configured to specify a reference region that is to be referenced at the determination in the medical image ( Miyasa Fig. 4, paragraph 0070, paragraph 0110 disclose diagnosis dedicated screen 400 illustrated in FIG. 4 includes a diagnostic target image display area 410 positioned on the left side, a medical reference information display area 420 on the right side, and a similar case display button 430 located at an upper right corner. The reason why similar cases are not present on the diagnosis dedicated screen 400 is because presenting the similar cases may be unnecessary if the diagnosis on the diagnostic target image is easy, as described in step S106 and paragraph 0116 Further, when the diagnosis is difficult, practical data of similar cases will be greatly helpful as reference information in the diagnosis rather than general information about diseases. Therefore, the display mode M.sub.2 illustrated in FIG. 5 includes the similar case display area 520 as a counterpart comparable to the medical reference information display area 420 illustrated in FIG. 4),
the determination unit determines whether or not the medical image is an image that is difficult to make a judgement about, based on a comparison between information regarding the reference region and a predetermined value (Miyasa Figs. 1-2 and 4 paragraph 0116 Further, when the diagnosis is difficult, practical data of similar cases will be greatly helpful as reference information in the diagnosis rather than general information about diseases. Therefore, the display mode M.sub.2 illustrated in FIG. 5 includes the similar case display area 520 as a counterpart comparable to the medical reference information display area 420 illustrated in FIG. 4 ), and
the search unit searches for the similar medical image when the determination unit determines that the medical image is an image that is difficult to make a judgement about (Miyasa Figs. 1, 2 and 4 paragraph 0060 display recommendation level calculation unit 105 is functionally configured to calculate a display recommendation level of the similar case data based on a medical practice difficulty level of the similar case data searched by the similar case search unit 104 (i.e., the diagnostic difficulty level in the present exemplary embodiment and paragraph 0061 disclose The medical reference information search unit 106 is functionally configured to search medical reference information, such as disease information, from the medical information database 230. The storage unit 107 stores various types of information acquired by the medical image acquisition unit 101, the feature information extraction unit 102, the previous image acquisition unit 103, the similar case search unit 104, the display recommendation level calculation unit 105, and the medical reference information search unit 106. This obviously corresponds to a search unit configured to search for a similar medical image that is similar to the medical image and when the medical image is determined as an image that is difficult to make a judgement about).
Regarding claim 4 Miyasa (US 20110099032) disclose he determination unit determines that the medical image is an image that is difficult to make a judgement about when the information regarding the reference region indicates a value that is lower than the predetermined value, and the search unit searches for the similar medical image when the determination unit determines that the medical image is an image that is difficult to make a judgement about (Figs 1-2 block S106-S107, paragraph 0093 In the present exemplary embodiment, a setting value of the first threshold T is equal to 0.5 (i.e., T=0.5). The determination processing of step S106 indicates that medical reference information search processing (i.e., processing in step S107) is performed only when the display recommendation level P of the diagnostic target image is less than the first threshold T and the preset image diagnosis is the first medical examination and also note paragraph 0101-0104).
Regarding claim 5 Miyasa (US 20110099032) disclose the information regarding the reference region includes information that indicates the number of pixels of the reference region, the area of the reference region, a ratio of the reference region to an image region of the medical image, or an image feature of the reference region (Miyasa Fig 4, paragraph 0070 disclose the feature information extraction unit 102 defines the extracted area as a "concerned area." Then, the feature information extraction unit 102 extracts image feature information relating to the affected part from the "concerned area" having been set. For example, when the affected part is a solitary nodule shade, the feature information extraction unit 102 extracts size information of the affected part (e.g., diameter (major diameter/minor diameter/average diameter) and area), shape features of the affected part (e.g., ratio of major diameter to minor diameter, ratio of border line length to average diameter, and fractal dimension of border line), average density of the affected part, and density distribution pattern of the affected part. The feature information extraction unit 102 can extract other various image feature information).
Regarding claim 6 Miyasa (US 20110099032) disclose an inference unit configured to output a classification result regarding whether or not the input medical image is an image that is difficult to make a judgement about regarding the radiological interpretation item (Myasa Fig. 1 and Fig. 2, blocks S105-S106, Fig.3 block, paragraph 0047 states "diagnostic difficulty level" of a medical case relating to a medical image similar to a diagnostic target medical image corresponds to a "diagnostic difficulty level" of the diagnostic target medical image. It is presumed that the necessity of presenting the similar case is variable depending on the "diagnostic difficulty level" and paragraph 0050 disclose information processing apparatus 100-1 performs processing for medical case data including examination information of various subjects (patients). The case database 210 is a medical case data storage unit configured to store medical case data, which include examination information of subjects in association with medical practice difficulty level information based on the examination information. More specifically, the case database 210 stores medical case data relating to medical practice completed (e.g., diagnosis completed and treatment completed) medical cases i.e. difficulty level is classification and also note: Miyasa Figs. 1-2 and 4 paragraph 0116),
the determination unit determines whether or not the medical image is an image that is difficult to make a judgement about regarding the radiological interpretation item, based on the classification result output from the inference unit (Miyasa Figs. 1-2 and 4 paragraph 0116 Further, when the diagnosis is difficult, practical data of similar cases will be greatly helpful as reference information in the diagnosis rather than general information about diseases. Therefore, the display mode M.sub.2 illustrated in FIG. 5 includes the similar case display area 520 as a counterpart comparable to the medical reference information display area 420 illustrated in FIG. 4 ), and
the search unit searches for the similar medical image when the determination unit determines that the medical image is an image that is difficult to make a judgement about (Miyasa Figs. 1, 2 and 4 paragraph 0060 display recommendation level calculation unit 105 is functionally configured to calculate a display recommendation level of the similar case data based on a medical practice difficulty level of the similar case data searched by the similar case search unit 104 (i.e., the diagnostic difficulty level in the present exemplary embodiment and paragraph 0061 disclose The medical reference information search unit 106 is functionally configured to search medical reference information, such as disease information, from the medical information database 230. The storage unit 107 stores various types of information acquired by the medical image acquisition unit 101, the feature information extraction unit 102, the previous image acquisition unit 103, the similar case search unit 104, the display recommendation level calculation unit 105, and the medical reference information search unit 106. This obviously corresponds to a search unit configured to search for a similar medical image that is similar to the medical image and when the medical image is determined as an image that is difficult to make a judgement about).
Regarding claim 7 Miyasa (JP 2014039852) disclose the search unit searches for a reference image that is similar to the medical image from among reference images in an image server, as a candidate image for the similar medical image, whether or not the medical image is an image that is difficult to make a judgement about is determined based on a comparison between information regarding the reference region in the reference image and the predetermined value, and when the medical image is determined as an image that is not difficult to make a judgement about, the reference image is selected as the similar medical image whose radiological interpretation item has a high degree of reliability (Miyasa, page 15, {second Embodiment}, lines 2-15 Miyasa disclose In the information processing apparatus 100-1 according to the first embodiment described above, the display recommendation degree P of the similar case is calculated based on the diagnosis difficulty level in the similar case. On the other hand, in the information processing apparatus 100-2 according to the second embodiment, the similarity is based on both the diagnosis difficulty level in a similar case and the disease determination difficulty level obtained by image analysis of the diagnosis target image. The case is different from the first embodiment in that the case recommendation degree P is calculated. Here, the “disease discrimination difficulty level” represents the degree of difficulty of disease discrimination performed by image analysis of the diagnosis target image. Thereby, even when the similarity of the similar case with respect to the diagnosis target image is low, that is, the reference degree of the similar case is low, the reliability of the display recommendation degree P is increased by increasing the weight of the disease determination difficult level, which is another index. Deterioration can be prevented)
Miyasa (US 20110099032) disclose when the medical image is determined as an image that is not difficult to make a judgement about, the reference image is selected as the similar medical image whose radiological interpretation item has a high degree of reliability (Miyasa Figs.1-2, blocks 104, 105 and 210).
Regarding claim 8 Miyasa (US 20110099032) disclose the search unit uses an image feature of the entire medical image or an image feature of a region of the medical image other than the reference region to search for the reference image that is similar to the medical image (Miyasa Figs. 1 blocks 104-106 and 4, paragraph 0070 disclose the feature information extraction unit 102 defines the extracted area as a "concerned area." Then, the feature information extraction unit 102 extracts image feature information relating to the affected part from the "concerned area" having been set. For example, when the affected part is a solitary nodule shade, the feature information extraction unit 102 extracts size information of the affected part (e.g., diameter (major diameter/minor diameter/average diameter) and area), shape features of the affected part (e.g., ratio of major diameter to minor diameter, ratio of border line length to average diameter, and fractal dimension of border line), average density of the affected part, and density distribution pattern of the affected part. The feature information extraction unit 102 can extract other various image feature information and paragraphs 0071-0072 Then, the feature information extraction unit 102 transmits the image feature information extracted from the diagnostic target image to the storage unit 107 and subsequently, in step S103, the similar case search unit 104 acquires the image feature information relating to the diagnostic target image stored in the storage unit 107 in step S102. Next, the similar case search unit 104 performs similar case search processing to extract, from the case database 210, medical case data having image feature information similar to the acquired image feature information relating to the diagnostic target image (which may be referred to as a similar case search step).
Regarding claim 9 Miyasa (JP 2014039852) disclose he search unit determines that the reference image is an image that is not difficult to make a judgement about when the information regarding the reference region is determined to indicate a value that is higher than or equal to the predetermined value, and selects the reference image as the similar medical image whose radiological interpretation item has a high degree of reliability. (Miyasa, page 15, {second Embodiment}, lines 2-15 Miyasa disclose
In the information processing apparatus 100-1 according to the first embodiment described above, the display recommendation degree P of the similar case is calculated based on the diagnosis difficulty level in the similar case. On the other hand, in the information processing apparatus 100-2 according to the second embodiment, the similarity is based on both the diagnosis difficulty level in a similar case and the disease determination difficulty level obtained by image analysis of the diagnosis target image. The case is different from the first embodiment in that the case recommendation degree P is calculated. Here, the “disease discrimination difficulty level” represents the degree of difficulty of disease discrimination performed by image analysis of the diagnosis target image. Thereby, even when the similarity of the similar case with respect to the diagnosis target image is low, that is, the reference degree of the similar case is low, the reliability of the display recommendation degree P is increased by increasing the weight of the disease determination difficult level, which is another index. Deterioration can be prevented).
Regarding claim 10 Miyasa (US 20110099032 ) disclose the information regarding the reference region in the reference image includes information that indicates the number of pixels of the reference region, the area of the reference region, a ratio of the reference region to an image region of the medical image, or an image feature of the reference region (Miyasa Figs. 1 and 4, paragraph 0070 disclose the feature information extraction unit 102 defines the extracted area as a "concerned area." Then, the feature information extraction unit 102 extracts image feature information relating to the affected part from the "concerned area" having been set. For example, when the affected part is a solitary nodule shade, the feature information extraction unit 102 extracts size information of the affected part (e.g., diameter (major diameter/minor diameter/average diameter) and area), shape features of the affected part (e.g., ratio of major diameter to minor diameter, ratio of border line length to average diameter, and fractal dimension of border line), average density of the affected part, and density distribution pattern of the affected part. The feature information extraction unit 102 can extract other various image feature information).
Regarding claim 11 Miyasa (US 20110099032) disclose additional information is added to each reference image included in the reference images, the additional information indicating a high degree of reliability determined in advance, and the search unit determines whether or not the reference image is an image that is difficult to make a judgement about, based on the additional information (Miyasa paragraph 0074, As illustrated in FIG. 3, the medical case data stored in the case database 210 according to the present exemplary embodiment includes identification information 310, clinical information 320, image information 330, diagnostic information 340, and diagnostic difficulty level information 350 paragraph 0075 More specifically, the medical case data according to the present exemplary embodiment includes examination information of a subject, which is, for example, composed of the identification information 310, the clinical information 320, the image information 330, and the diagnostic information 340. The examination information of each subject is stored in association with the diagnostic difficulty level information 350 that represents a medical practice difficulty level and paragraph 0084 the similar case search unit 104 transmits the k pieces of similar case data acquired by the similar case search processing to the display recommendation level calculation unit 105 and the storage unit 107 and paragraph 0166 disclose Further, if the physician's specialized region is chest, the diagnostic target image attributes coincide with the physician's specialty in the region. Therefore, an addition value "0" is set. Further, for example, if the physician's specialized region is abdomen, head, or breast, the purpose of performing image diagnosis may be different. Therefore, an addition value "0.15" is set. If the physician's specialized region is any other one (e.g., doing nothing about image diagnosis), an addition value "0.3" is set. . In the system of Miyasa therefore it would be obvious to include reliability information because of diagnostic information how much reliable/accurate is diagnostic information).
Regarding claim 12 Miyasa (US 20110099032) disclose the display control unit displays, on the display unit, information regarding the reference region in the medical image and information regarding the reference region in the similar medical image (Miyasa Fig. 1, blocks 105, 106 and 108 Figs 2 and 4) .
Regarding claim 13 Miyasa (US 20110099032) disclose the medical image is an image obtained by capturing mammary glands of an object, and the radiological interpretation item is a classification based on a mammary gland density of the object (Miyasa Figs. 1-2 Miyasa paragraph 0074, As illustrated in FIG. 3, the medical case data stored in the case database 210 according to the present exemplary embodiment includes identification information 310, clinical information 320, image information 330, diagnostic information 340, and diagnostic difficulty level information 350 paragraph 0075 More specifically, the medical case data according to the present exemplary embodiment includes examination information of a subject, which is, for example, composed of the identification information 310, the clinical information 320, the image information 330, and the diagnostic information 340, paragraph 0007 disclose further, as another conventional CAD technique, there is a conventional technique capable of automatically diagnosing malignancy or disease type about detected abnormal shadow candidates. An example method for realizing the above-described CAD technique is the mammography that estimates a malignancy level of a breast cancer using a Bayesian network and paragraph 0166 disclose Further, if the physician's specialized region is chest, the diagnostic target image attributes coincide with the physician's specialty in the region. Therefore, an addition value "0" is set. Further, for example, if the physician's specialized region is abdomen, head, or breast, the purpose of performing image diagnosis may be different. Therefore, an addition value "0.15" is set. If the physician's specialized region is any other one (e.g., doing nothing about image diagnosis), an addition value "0.3" is set. Therefore in the system of Miyasa it is obvious that the medical image is an image obtained by capturing mammary glands of an object, and the radiological interpretation item is a classification based on a mammary gland density of the object)
Regarding claim 14 Miyasa (US 20110099032) disclose identification information regarding the radiological interpretation item includes information indicating the classification or information regarding the mammary gland density. (Miyasa paragraph 0074, As illustrated in FIG. 3, the medical case data stored in the case database 210 according to the present exemplary embodiment includes identification information 310, clinical information 320, image information 330, diagnostic information 340, and diagnostic difficulty level information 350 paragraph 0075 More specifically, the medical case data according to the present exemplary embodiment includes examination information of a subject, which is, for example, composed of the identification information 310, the clinical information 320, the image information 330, and the diagnostic information 340. The examination information of each subject is stored in association with the diagnostic difficulty level information 350 that represents a medical practice difficulty level and paragraph 0084 the similar case search unit 104 transmits the k pieces of similar case data acquired by the similar case search processing to the display recommendation level calculation unit 105 and the storage unit 107, paragraph 0007 disclose further, as another conventional CAD technique, there is a conventional technique capable of automatically diagnosing malignancy or disease type about detected abnormal shadow candidates. An example method for realizing the above-described CAD technique is the mammography that estimates a malignancy level of a breast cancer using a Bayesian network and paragraph 0166 disclose Further, if the physician's specialized region is chest, the diagnostic target image attributes coincide with the physician's specialty in the region. Therefore, an addition value "0" is set. Further, for example, if the physician's specialized region is abdomen, head, or breast, the purpose of performing image diagnosis may be different. Therefore, an addition value "0.15" is set. If the physician's specialized region is any other one (e.g., doing nothing about image diagnosis), an addition value "0.3" is set. Therefore in the system of Miyasa it is obvious that identification information regarding the radiological interpretation item includes information indicating the classification or information regarding the mammary gland density.)
Regarding claim 16 Miyasa (JP 2014039852) disclose the search unit searches an image server that stores reference images whose radiological interpretation item has a high degree of reliability, for the similar medical image that is similar to the medical image (Miyasa, page 15, {second Embodiment}, lines 2-15 Miyasa disclose
In the information processing apparatus 100-1 according to the first embodiment described above, the display recommendation degree P of the similar case is calculated based on the diagnosis difficulty level in the similar case. On the other hand, in the information processing apparatus 100-2 according to the second embodiment, the similarity is based on both the diagnosis difficulty level in a similar case and the disease determination difficulty level obtained by image analysis of the diagnosis target image. The case is different from the first embodiment in that the case recommendation degree P is calculated. Here, the “disease discrimination difficulty level” represents the degree of difficulty of disease discrimination performed by image analysis of the diagnosis target image. Thereby, even when the similarity of the similar case with respect to the diagnosis target image is low, that is, the reference degree of the similar case is low, the reliability of the display recommendation degree P is increased by increasing the weight of the disease determination difficult level, which is another index. Deterioration can be prevented).
Regarding claim 20 Miyasa (US 20110099032) disclose A non-transitory computer-readable storage medium storing a program for causing a computer to execute the method according to claim 18 (Fig 1-2 and 9 and paragraph 0277-0278).
Communication Any inquiry concerning this communication or earlier communications from the examiner should be directed to ISHRAT I SHERALI whose telephone number is (571)272-7398. The examiner can normally be reached Monday-Friday 8:00AM -5:00 PM.
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ISHRAT I. SHERALI
Examiner
Art Unit 2667
/ISHRAT I SHERALI/Primary Examiner, Art Unit 2667