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 .
DETAILED ACTION
1. A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 2/13/2026 has been entered.
Claim Rejections - 35 USC § 101
2. The previous rejections of the claims under 35 USC 101 are withdrawn in response to Applicant’s amendments to the claims filed on 2/13/2026 that have been determined by the Examiner to not be directed towards an abstract idea without significantly more and are therefore eligible subject matter.
Response to Arguments
3. Applicant’s arguments with respect to the previously pending claims have been fully considered but they are moot in view of new ground(s) of rejection necessitated by Applicant’s amendments to the pending claims.
Additionally, it is noted that the Applicant argues that the previously applied Halmann reference fails to teach the claimed limitation of “determining one or more values of one or more morphological features of the at least one pleural line region by fitting a function to measured values associated with the at least one pleural line region” since the data in Halmann is either a brightness values of a given pixel or location data. The Examiner notes that Halmann discloses (paragraphs 0051-0052) that calculation of an irregularity score for the segmented/identified pleural line regions being calculated that includes a jumpiness score that is dependent upon the width/size of the vertical gaps in the pleural lines where the vertical gap refers to the number of pixels vertically between a lower/upper border at the given pixel location relative to a neighboring pixel. This vertical gap measurement is used in order to calculate the jumpiness score which is an evaluation amount calculated based on the vertical gap amount where the greater the vertical gap, the higher the score. The resulting jumpiness score is used to further calculate an irregularity score for each pixel within the pleural line. Therefore, based on the disclosure of Halmann and the broadest reasonable interpretation of the scope of the limitations contained within the pending claims, it is concluded that the calculation of the jumpiness score evaluating the vertical gaps within the pleural line regions fully anticipates the limitation of “determining one or more values of one or more morphological features of the at least one pleural line region by fitting a function to measured values associated with the at least one pleural line region”.
Claim Rejections – 35 USC § 103
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 of this title, 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.
4. Claims 1-8 and 10-20 are rejected under 35 U.S.C 103 as being unpatentable by Halmann (US PGPub 2022/0061813) [hereafter Halmann] in view of Casciaro (US PGPub 2024/0252140) [hereafter Casciaro].
5. As to claim 1, Halmann discloses a method (operational method shown in Figure 3 which is executed by an ultrasound imaging system shown in Figure 1 including medical image processing system shown in Figure 2), comprising: receiving imaging data (ultrasound lung image as shown in Figures 4-7) indicative of a lung of a subject; determining at least one pleural line region in the imaging data (410-422 as shown in Figure 4) by performing a segmentation process (image recognition/shape and edge detection/convolutional detection and quantification operations) across a plurality of pixels of the imaging data; determining one or more values (jumpiness score and irregularity score) of one or more morphological features (local dimness, vertical location, orientation, change between frames, vertical gaps, discontinuous appearance, etc.) of the at least one pleural line region by fitting a function to measured values associated with the at least one pleural line region; and sending, based on the one or more values of one or more morphological features, an indication of a condition of the lung (formation and output of an annotated ultrasound image and suggested diagnosis to a display) (Paragraphs 0019, 0030-0034, 0037-0039, 0043, 0047-0054, 0060-0062).
It is however noted that Halmann fails to particularly disclose an indication of a condition of the lung comprising at least an indication of a severity of a disease.
On the other hand, Casciaro discloses sending, based on one or more values of one or more morphological features, an indication of a condition of a lung comprising at least an indication of a severity of a disease (pneumonia) (Paragraphs 0010, 0025, 0031-0032, 0113, 0127, 0140-0141, 0157, 0174).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to include providing an indication of a condition of the lung comprising at least an indication of a severity of a disease as ataught by Casciaro with the method and corresponding operational device of Halmann because the cited prior art references are directed towards imaging devices that acquire images of a patients lung and diagnose conditions of the lung based upon characteristics of the acquired images and because each of the claimed limitations is fully disclosed within the cited prior art references and would yield predictable results of allowing an objective disease severity staging and early identification of COVID-19 possible presence before the onset of pulmonary fibrosis in asymptomatic patients.
6. As to claim 2, Halmann discloses the indication of the condition comprises an indication of one or more of a disease, a level of a disease, a viral disease, pneumonia, coronavirus disease, or a COVID-19 infection (Paragraphs 0060-0062).
7. As to claim 3, Halmann discloses the indication of the condition of the lung comprises one or more of an indication of one or more of the values of the one or more morphological features or an indication of a value determined based on one or more of the determined values of the one or more morphological features (Paragraphs 0052-0054, 0060-0062).
8. As to claim 4, Halmann discloses the imaging data comprises lung ultrasound imaging data (Paragraphs 0019, 0033, 0043-0046).
9. As to claim 5, Halmann discloses the one or more morphological features comprise one or more of thickness, thickness variation, tortuosity, nonlinearity, or projected intensity variation (Paragraphs 0033, 0047-0048, 0051-0052).
10. As to claim 6, Halmann discloses determining the one or more values of the one or more morphological features of the at least one pleural line region comprises performing feature extraction of a portion of the imaging data comprising the at least one pleural line region (Paragraphs 0032-0034, 0047-0048).
11. As to claim 7, Halmann discloses sending the indication of the condition of the lung comprises one or more of sending the indication to a computing device, sending the indication to storage, or causing the indication of the condition to be output to via a display (Paragraphs 0038, 0053-0057, 0062).
12. As to claim 8, Halmann discloses determining the at least one pleural line region in the imaging data comprises performing automatic segmentation of the imaging data to detect the at least one pleural line region (Paragraphs 0032-0034, 0047-0048).
13. As to claim 10, Halmann discloses the pleural line region comprises a region of tissue having features within a threshold similarity to a line (as shown in Figure 4) (Paragraphs 0032-0034, 0047-0048).
14. As to claim 11, Halmann discloses determining the one or more values of the one or more morphological features comprises one or more of measuring or calculating of a value of a corresponding morphological feature based on intensity values of pixels of the imaging data comprising the pleural line region (Paragraphs 0032-0034, 0047-0048, 0051-0052).
15. As to claim 12, Halmann discloses determining, based on applying one or more of a rule or a model to the one or more values of the morphological features, the indication of the condition (Paragraphs 0032-0034, 0051-0052).
16. As to claim 13, Halmann discloses the one or more morphological features of the at least one pleural line region comprise features indicative of variations in one or more of shape or linearity of the at least one pleural line region (Paragraphs 0032-0033, 0047-0048, 0051-0052).
17. As to claim 14, Halmann discloses training, based on a set of training images, a machine learning model configured to associate values of the one or more morphological features with corresponding indications of the condition, wherein the indication of the condition is determined based on the machine learning model (Paragraphs 0032-0034, 0051-0052).
18. As to claim 15, Halmann discloses determining, based on inputting the one or more values of the one or more morphological features to a machine learning model, the indication of the condition (Paragraphs 0032-0034, 0051-0052).
19. As to claim 16, Halmann discloses applying weights to each of the one or more values of the one or more morphological features, wherein the weights are applied equally or based on a machine learning model; and averaging the weighted values to determine a value of the indication of the condition (irregularity score) (Paragraphs 0032-0034, 0051-0052).
20. As to claims 17-20, the combination of the Halmann and Casciaro references discloses all claimed subject matter as explained with respect to the above comments/citations of claims 1 and 5.
21. Claim 9 is rejected under 35 U.S.C 103 as being unpatentable by Halmann (US PGPub 2022/0061813) [hereafter Halmann] and Casciaro (US PGPub 2024/0252140) [hereafter Casciaro] in further view of Xu (US PGPub 2020/0359991) [hereafter Xu].
22. As to claim 9, it is noted that Halmann and Casciaro fails to particularly disclose determining the at least one pleural line region in the imaging data comprises receiving, based on user input, an indication of a location of the at least one pleural line region and segmenting, based on the indication of the location, the pleural line region.
On the other hand, Xu discloses determining the at least one pleural line region (as shown in Figures 3 and 10) in the imaging data comprises receiving, based on user input, an indication of a location of the at least one pleural line region and segmenting, based on the indication of the location, the pleural line region (Paragraphs 0036-0037, 0042-0044, 0046, 0065-0071).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to include determining the at least one pleural line region in the imaging data comprises receiving, based on user input, an indication of a location of the at least one pleural line region and segmenting, based on the indication of the location, the pleural line region as taught by Xu with the operational method of Halmann and Casciaro because the cited prior art are directed towards ultrasound imaging methods and systems that identify pleural line regions of lung images in order to diagnose irregularities/diseases present within the images and because each of the claimed limitations are fully disclosed within the cited prior art reference and would yield predictable results of enabling a certified user/expert to manually identify the area including the pleural line to be used for the identification of the lung condition.
Conclusion
23. Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL S OSINSKI whose telephone number is (571) 270-3949. The examiner can normally be reached on Monday - Thursday, 10:00am - 6:00pm. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Oneal Mistry can be reached on (313) 446-4912. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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MO
/MICHAEL S OSINSKI/Primary Examiner, Art Unit 2674
2/18/2026