DETAILED ACTION
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 .
Response to Arguments
Applicant’s arguments, see the Pre-Appeal Brief, filed 09 March 2026, with respect to the rejection(s) of claims 1-22 under Darty et al. (WO2017/201093) have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of a newly found prior art reference.
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 (i.e., changing from AIA to pre-AIA ) 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 1-18 and 20-22 are rejected under 35 U.S.C. 103 as being unpatentable over Munoz (U.S. Patent Application Publication 2016/0157725) in view of Bala et al. (U.S. Application Publication 2017/0303790).
Regarding claim 1, Munoz discloses a mobile imaging system (Fig. 2), comprising: a smartphone (Fig. 10 – mobile phone); a camera system including: a smartphone camera integrated into the smartphone (Fig. 10 – mobile phone; paragraph [0132] – the portable device of Fig. 10 includes a hyperspectral imager 110 and a camera 140 (e.g., a visible, and IR imager) – in a particular embodiment, a fisheye camera 140 of a mobile device 50 takes a RGB image of the region of interest, an IR camera 140 takes a laser speckle image of the region of interest, and a hyperspectral camera 110 takes a hyperspectral image of the region of interest); which is configured for taking images using the smartphone camera at a predetermined range of wavelengths including visible, near-infrared, and infrared wavelengths (Fig. 9 – infrared; paragraph [0079] – infrared; paragraph [0082] - visible and near-infrared); and an infrared camera configured to capture images in an infrared light spectrum (Fig. 10 – mobile phone; paragraph [0132] – the portable device of Fig. 10 includes a hyperspectral imager 110 and a camera 140 (e.g., a visible, and IR imager) – in a particular embodiment, a fisheye camera 140 of a mobile device 50 takes a RGB image of the region of interest, an IR camera 140 takes a laser speckle image of the region of interest, and a hyperspectral camera 110 takes a hyperspectral image of the region of interest); an illumination module activatable to emit light (paragraph [0025] – the at least one light source is at least one of a light emitting diode (LED) and a laser); a computer system including processing circuitry including executable code configured to collect multispectral imaging data of biological tissue using the smartphone camera and the infrared camera, and to process the multispectral imaging data (paragraphs [0030], [0034], [0036], and [0038] - the computer analytics program can perform the aggregation of image data…synthesis of image data reports for clinical care, patient and clinical meta-data, direct and/or indirect interface with healthcare related software programs and portals, clinical meta-data reports, statistical modeling, and machine learning capabilities…acquiring the raw laser speckle image and hyperspectral image and 3D surface image of a tissue region of interest of a subject in need thereof; and analyze and monitor the tissue region of interest, and optionally diagnosing, triaging, intervening, and/or treating the subject having tissue pathology); a battery (paragraph [0029] – rechargeable battery; paragraph [0100] – the device or system further comprises at least one power source, e.g., a battery); and a housing (Fig. 10; paragraph [0024] – housing). However, Munoz fails to disclose a filter assembly configured to movably position a plurality of optical filters with respect to the smartphone camera, wherein each optical filter of the filter assembly is configured for taking images using the smartphone camera at a predetermined range of wavelengths including visible and near-infrared wavelengths.
Referring to the Bala et al. reference, Bala et al. discloses a mobile imaging system, comprising: a filter assembly configured to movably position a plurality of optical filters with respect to the smartphone camera (Bala et al.: Figs. 9 and 10; paragraph [0049] – Fig. 9, a diagram shows a sleeve used for a mobile device implementing a hyperspectral camera system having multiple cameras on a rear side, wherein the inside portion of the sleeve of Fig. 9 is shown in Fig. 10 – as shown in Fig. 9, a sleeve 902, also commonly known as a cover or case, attachable to the device 200, containing a rotating wheel may be placed over the camera 302 and an opening 904 is provided for the flash array 304 – more particularly, a rotating filter wheel 906 comprises a plurality of filters 908, each of which may be aligned with the lens of the camera – by providing a movable wheel as shown, different filters may be selected without having to physically remove and replace a filter attachment for the device – a second aperture 914 is provided for the lens of the camera 303 – camera 303 may be an RGB camera, while the camera 302 will be determined based upon the selected filter of the filter wheel 906), wherein each optical filter of the filter assembly is configured for taking images using the smartphone camera at a predetermined range of wavelengths including visible and near-infrared wavelengths (Bala et al.: Figs. 9 and 10; paragraph [0040] – a mobile hyperspectral camera system that is built into a standard consumer device such as a smartphone or tablet can offer many beneficial applications to a consumer – for example, an image of a person’s face captured under near infra-red (NIR) illumination produces smooth pleasing skin tones, and can thus be combined with RGB images to enhance selfie images – combining NIR and RGB images can also offer improved biometrics capabilities – facial images taken under ultra-violet (UV) light reveal useful features indicative of skin health and aging – incorporating such technologies into a common consumer mobile device such as a smartphone enables a rich suite of applications that can combine the power of hyperspectral imaging with contextual knowledge already available on the device, such as the user’s environment, lifestyle, and activities; paragraph [0049] – Fig. 9, a diagram shows a sleeve used for a mobile device implementing a hyperspectral camera system having multiple cameras on a rear side, wherein the inside portion of the sleeve of Fig. 9 is shown in Fig. 10 – as shown in Fig. 9, a sleeve 902, also commonly known as a cover or case, attachable to the device 200, containing a rotating wheel may be placed over the camera 302 and an opening 904 is provided for the flash array 304 – more particularly, a rotating filter wheel 906 comprises a plurality of filters 908, each of which may be aligned with the lens of the camera – by providing a movable wheel as shown, different filters may be selected without having to physically remove and replace a filter attachment for the device – a second aperture 914 is provided for the lens of the camera 303 – camera 303 may be an RGB camera, while the camera 302 will be determined based upon the selected filter of the filter wheel 906).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have had included a filter assembly configured to movably position a plurality of optical filters with respect to the smartphone camera as disclosed by Bala et al. in the system disclosed by Munoz in order to enhance the smartphone camera that is integrated into the smartphone and to allow the user to select the appropriate filter thereby providing a robust, cost-effective non-invasive and rapid imaging-based method or device for collecting data.
Regarding claim 2, Munoz in view of Bala et al. discloses all of the limitations as previously discussed with respect to claim 1 including that wherein the processing circuitry is configured to quantify a physical characteristic of biological tissue associated with an injury or ailment (Munoz: paragraph [0056] – embodiments of the present invention provide a three dimensional reconstruction of visual and anatomical data and augmentation of color spectral patterns that serve as spectral fingerprints of distinct tissue types and characteristics acquired from an area of interest, which facilitates an early evaluation of tissue pathology (e.g., malignancies, ulcers, eschars, scabs, wounds, etc.) and tissue healing and regeneration in, for example, wounds, thereby providing early disease detection, promoting earlier interventions and reducing the number of complications with tissue pathologies and the number of advanced interventions that result from wound complications and other tissue pathologies).
Regarding claim 3, Munoz in view of Bala et al. discloses all of the limitations as previously discussed with respect to claim 1 including that wherein processing circuitry is configured to compare a value or range of a quantified physical characteristic to a library of threshold values or ranges (Munoz: paragraphs [0090], [0107], and [0110]; paragraph [0164] – as more information is gathered as a spectral library is compiled and techniques are refined and such information can be evaluated with deep learning and computer learning to investigate patterns and derive statistical significance between specific patterns and clinical information – the system has the capability to become a diagnostic device as it relates to tissue pathology, tissue healing and tissue regeneration).
Regarding claim 4, Munoz in view of Bala et al. discloses all of the limitations as previously discussed with respect to claim 1 including that wherein the computer system includes the smartphone with a user interface configured to output user instructions and receive user inputs to control the system (Munoz: paragraph [0016] - mobile device and software; paragraph [0038] - providing a handheld device or the system with a software analytics program; paragraph [0068] – user interface – a user may select the particular raw, processed, or analyzed data for viewing via a graphical user interface (GUI)).
Regarding claim 5, Munoz in view of Bala et al. discloses all of the limitations as previously discussed with respect to claim 1 including that wherein the plurality of optical filters includes one of a spectral filter, a bandpass filter, a dual-bandpass filter, a polarization filter, a visible filter, an ultraviolet filter, or a reference filter (Munoz: paragraphs [0082] and [0107]).
Regarding claim 6, Munoz in view of Bala et al. discloses all of the limitations as previously discussed with respect to claim 1 including that wherein the smartphone camera is configured to capture images in visible and near-infrared light spectra (Munoz: Fig. 9; paragraph [0082]; Figs. 9 and 10; paragraph [0040] – a mobile hyperspectral camera system that is built into a standard consumer device such as a smartphone or tablet can offer many beneficial applications to a consumer – for example, an image of a person’s face captured under near infra-red (NIR) illumination produces smooth pleasing skin tones, and can thus be combined with RGB images to enhance selfie images – combining NIR and RGB images can also offer improved biometrics capabilities – facial images taken under ultra-violet (UV) light reveal useful features indicative of skin health and aging – incorporating such technologies into a common consumer mobile device such as a smartphone enables a rich suite of applications that can combine the power of hyperspectral imaging with contextual knowledge already available on the device, such as the user’s environment, lifestyle, and activities; paragraph [0049] – Fig. 9, a diagram shows a sleeve used for a mobile device implementing a hyperspectral camera system having multiple cameras on a rear side, wherein the inside portion of the sleeve of Fig. 9 is shown in Fig. 10 – as shown in Fig. 9, a sleeve 902, also commonly known as a cover or case, attachable to the device 200, containing a rotating wheel may be placed over the camera 302 and an opening 904 is provided for the flash array 304 – more particularly, a rotating filter wheel 906 comprises a plurality of filters 908, each of which may be aligned with the lens of the camera – by providing a movable wheel as shown, different filters may be selected without having to physically remove and replace a filter attachment for the device – a second aperture 914 is provided for the lens of the camera 303 – camera 303 may be an RGB camera, while the camera 302 will be determined based upon the selected filter of the filter wheel 906).
Regarding claim 7, Munoz in view of Bala et al. discloses all of the limitations as previously discussed with respect to claims 1 and 6 including that wherein the filter assembly includes: a base fixedly connected to the housing; and a filter member adjustably connected to the base and including the plurality of optical filters, wherein the filter member is translatable or rotatable to sequentially position each of plurality of optical filters proximally to the first camera (Munoz: Fig. 10; paragraph [0078]; Bala et al.: Figs. 9 and 10; paragraph [0040] – a mobile hyperspectral camera system that is built into a standard consumer device such as a smartphone or tablet can offer many beneficial applications to a consumer – for example, an image of a person’s face captured under near infra-red (NIR) illumination produces smooth pleasing skin tones, and can thus be combined with RGB images to enhance selfie images – combining NIR and RGB images can also offer improved biometrics capabilities – facial images taken under ultra-violet (UV) light reveal useful features indicative of skin health and aging – incorporating such technologies into a common consumer mobile device such as a smartphone enables a rich suite of applications that can combine the power of hyperspectral imaging with contextual knowledge already available on the device, such as the user’s environment, lifestyle, and activities; paragraph [0049] – Fig. 9, a diagram shows a sleeve used for a mobile device implementing a hyperspectral camera system having multiple cameras on a rear side, wherein the inside portion of the sleeve of Fig. 9 is shown in Fig. 10 – as shown in Fig. 9, a sleeve 902, also commonly known as a cover or case, attachable to the device 200, containing a rotating wheel may be placed over the camera 302 and an opening 904 is provided for the flash array 304 – more particularly, a rotating filter wheel 906 comprises a plurality of filters 908, each of which may be aligned with the lens of the camera – by providing a movable wheel as shown, different filters may be selected without having to physically remove and replace a filter attachment for the device – a second aperture 914 is provided for the lens of the camera 303 – camera 303 may be an RGB camera, while the camera 302 will be determined based upon the selected filter of the filter wheel 906).
Regarding claim 8, Munoz in view of Bala et al. discloses all of the limitations as previously discussed with respect to claims 1, 6, and 7 including that wherein the illumination module includes a controller configurable to control any of: a wavelength of light to be emitted by the illumination module; a number of different wavelengths of light to be emitted; a cycle length of the illumination module, wherein the cycle length is a time period between activation and deactivation of the illumination module; and a cycle quantity of the illumination module, wherein the cycle quantity is a number of cycles the illumination module is configured to perform (Munoz: paragraphs [0080], [0082], [0083], [0088], [0106], and [0107]).
Regarding claim 9, Munoz in view of Bala et al. discloses all of the limitations as previously discussed with respect to claim 1 including that wherein the illumination module is configured to sequentially emit light in at least three different wavelengths, and wherein the filter assembly includes at least three optical filters each configured for use during emission of one of the at least three different wavelengths of light that the illumination module is configured to emit (Munoz: paragraphs [0068]-[0073] and [0160]).
Regarding claim 10, Munoz in view of Bala et al. discloses all of the limitations as previously discussed with respect to claims 1 and 9 including that wherein the at least three different wavelengths are about 405, about 760, and about 850 nanometers (Munoz: paragraphs [0025], [0071], [0072], [0077], [0081], and [0088]).
Regarding claim 11, Munoz discloses a mobile imaging system (Fig. 2), comprising: a smartphone (Fig. 10 – mobile phone); a camera system including: a smartphone camera integrated into the smartphone (Fig. 10 – mobile phone; paragraph [0132] – the portable device of Fig. 10 includes a hyperspectral imager 110 and a camera 140 (e.g., a visible, and IR imager) – in a particular embodiment, a fisheye camera 140 of a mobile device 50 takes a RGB image of the region of interest, an IR camera 140 takes a laser speckle image of the region of interest, and a hyperspectral camera 110 takes a hyperspectral image of the region of interest), the smartphone camera configured to capture images in a visible light spectrum, in a near-infrared light spectrum, and in an infrared spectrum (Fig. 9 – infrared; paragraph [0079] – infrared; paragraph [0082] - visible and near-infrared); an infrared camera configured to capture images in an infrared light spectrum (Fig. 10 – mobile phone; paragraph [0132] – the portable device of Fig. 10 includes a hyperspectral imager 110 and a camera 140 (e.g., a visible, and IR imager) – in a particular embodiment, a fisheye camera 140 of a mobile device 50 takes a RGB image of the region of interest, an IR camera 140 takes a laser speckle image of the region of interest, and a hyperspectral camera 110 takes a hyperspectral image of the region of interest); an illumination module including at least two light emitters configured to emit light at different wavelengths (paragraph [0025] - the at least one light source is at least one of a light emitting diode (LED) and a laser); a computer system including processing circuitry configured to execute instructions to control the camera system to collect multispectral imaging data including a plurality of near-infrared and infrared images of biological tissue and to process the multispectral imaging data (paragraphs [0030], [0034], [0036], and [0038] - the computer analytics program can perform the aggregation of image data…synthesis of image data reports for clinical care, patient and clinical meta-data, direct and/or indirect interface with healthcare related software programs and portals, clinical meta-data reports, statistical modeling, and machine learning capabilities…acquiring the raw laser speckle image and hyperspectral image and 3D surface image of a tissue region of interest of a subject in need thereof; and analyze and monitor the tissue region of interest, and optionally diagnosing, triaging, intervening, and/or treating the subject having tissue pathology); a battery paragraph [0029] – rechargeable battery; paragraph [0100] – the device or system further comprises at least one power source, e.g., a battery); and a housing (Fig. 10; paragraph [0024] – housing). However, Munoz fails to disclose a filter assembly including at least two optical filters selectively positionable with respect to the smartphone camera, the two optical filters including a first optical filter configured for capturing the images in the visible light spectrum using the smartphone camera and a second optical filter configured for capturing the images in the near-infrared light spectrum using the smartphone camera.
Referring to the Bala et al. reference, Bala et al. discloses a mobile imaging system, comprising: a filter assembly including at least two optical filters selectively positionable with respect to the smartphone camera (Bala et al.: Figs. 9 and 10; paragraph [0040] – a mobile hyperspectral camera system that is built into a standard consumer device such as a smartphone or tablet can offer many beneficial applications to a consumer – for example, an image of a person’s face captured under near infra-red (NIR) illumination produces smooth pleasing skin tones, and can thus be combined with RGB images to enhance selfie images – combining NIR and RGB images can also offer improved biometrics capabilities – facial images taken under ultra-violet (UV) light reveal useful features indicative of skin health and aging – incorporating such technologies into a common consumer mobile device such as a smartphone enables a rich suite of applications that can combine the power of hyperspectral imaging with contextual knowledge already available on the device, such as the user’s environment, lifestyle, and activities; paragraph [0049] – Fig. 9, a diagram shows a sleeve used for a mobile device implementing a hyperspectral camera system having multiple cameras on a rear side, wherein the inside portion of the sleeve of Fig. 9 is shown in Fig. 10 – as shown in Fig. 9, a sleeve 902, also commonly known as a cover or case, attachable to the device 200, containing a rotating wheel may be placed over the camera 302 and an opening 904 is provided for the flash array 304 – more particularly, a rotating filter wheel 906 comprises a plurality of filters 908, each of which may be aligned with the lens of the camera – by providing a movable wheel as shown, different filters may be selected without having to physically remove and replace a filter attachment for the device – a second aperture 914 is provided for the lens of the camera 303 – camera 303 may be an RGB camera, while the camera 302 will be determined based upon the selected filter of the filter wheel 906), the two optical filters including a first optical filter configured for capturing the images in the visible light spectrum using the smartphone camera and a second optical filter configured for capturing the images in the near-infrared light spectrum using the smartphone camera (Bala et al.: Figs. 9 and 10; paragraph [0040] – a mobile hyperspectral camera system that is built into a standard consumer device such as a smartphone or tablet can offer many beneficial applications to a consumer – for example, an image of a person’s face captured under near infra-red (NIR) illumination produces smooth pleasing skin tones, and can thus be combined with RGB images to enhance selfie images – combining NIR and RGB images can also offer improved biometrics capabilities – facial images taken under ultra-violet (UV) light reveal useful features indicative of skin health and aging – incorporating such technologies into a common consumer mobile device such as a smartphone enables a rich suite of applications that can combine the power of hyperspectral imaging with contextual knowledge already available on the device, such as the user’s environment, lifestyle, and activities; paragraph [0049] – Fig. 9, a diagram shows a sleeve used for a mobile device implementing a hyperspectral camera system having multiple cameras on a rear side, wherein the inside portion of the sleeve of Fig. 9 is shown in Fig. 10 – as shown in Fig. 9, a sleeve 902, also commonly known as a cover or case, attachable to the device 200, containing a rotating wheel may be placed over the camera 302 and an opening 904 is provided for the flash array 304 – more particularly, a rotating filter wheel 906 comprises a plurality of filters 908, each of which may be aligned with the lens of the camera – by providing a movable wheel as shown, different filters may be selected without having to physically remove and replace a filter attachment for the device – a second aperture 914 is provided for the lens of the camera 303 – camera 303 may be an RGB camera, while the camera 302 will be determined based upon the selected filter of the filter wheel 906).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have had included a filter assembly configured to movably position a plurality of optical filters with respect to the smartphone camera as disclosed by Bala et al. in the system disclosed by Munoz in order to enhance the smartphone camera that is integrated into the smartphone and to allow the user to select the appropriate filter thereby providing a robust, cost-effective non-invasive and rapid imaging-based method or device for collecting data.
Regarding claim 12, Munoz in view of Bala et al. discloses all of the limitations as previously discussed with respect to claim 11 including that wherein the filter assembly includes a mechanism configured to sequentially position the at least two optical filters proximally to the first camera during emission of light in at least two different wavelengths (Munoz: Fig. 10; paragraph [0082]; Bala et al.: Figs. 9 and 10; paragraph [0040] – a mobile hyperspectral camera system that is built into a standard consumer device such as a smartphone or tablet can offer many beneficial applications to a consumer – for example, an image of a person’s face captured under near infra-red (NIR) illumination produces smooth pleasing skin tones, and can thus be combined with RGB images to enhance selfie images – combining NIR and RGB images can also offer improved biometrics capabilities – facial images taken under ultra-violet (UV) light reveal useful features indicative of skin health and aging – incorporating such technologies into a common consumer mobile device such as a smartphone enables a rich suite of applications that can combine the power of hyperspectral imaging with contextual knowledge already available on the device, such as the user’s environment, lifestyle, and activities; paragraph [0049] – Fig. 9, a diagram shows a sleeve used for a mobile device implementing a hyperspectral camera system having multiple cameras on a rear side, wherein the inside portion of the sleeve of Fig. 9 is shown in Fig. 10 – as shown in Fig. 9, a sleeve 902, also commonly known as a cover or case, attachable to the device 200, containing a rotating wheel may be placed over the camera 302 and an opening 904 is provided for the flash array 304 – more particularly, a rotating filter wheel 906 comprises a plurality of filters 908, each of which may be aligned with the lens of the camera – by providing a movable wheel as shown, different filters may be selected without having to physically remove and replace a filter attachment for the device – a second aperture 914 is provided for the lens of the camera 303 – camera 303 may be an RGB camera, while the camera 302 will be determined based upon the selected filter of the filter wheel 906).
Regarding claim 13, Munoz in view of Bala et al. discloses all of the limitations as previously discussed with respect to claim 11 including that wherein the processing circuitry is configured to quantify a physical characteristic including any of tissue edema or swelling, tissue oxygenation, tissue perfusion, bacterial load, bioburden, a wound area, or a wound volume (Munoz: paragraph [0056] – embodiments of the present invention provide a three dimensional reconstruction of visual and anatomical data and augmentation of color spectral patterns that serve as spectral fingerprints of distinct tissue types and characteristics acquired from an area of interest, which facilitates an early evaluation of tissue pathology (e.g., malignancies, ulcers, eschars, scabs, wounds, etc.) and tissue healing and regeneration in, for example, wounds, thereby providing early disease detection, promoting earlier interventions and reducing the number of complications with tissue pathologies and the number of advanced interventions that result from wound complications and other tissue pathologies; paragraph [0067] – the device can also determine degrees of tissue oxygenation, spectral signatures, cellular and molecular signatures of a particular type of tissue and tissue pathology (e.g., a particular type of ulcer or malignancy)).
Regarding claim 14, Munoz in view of Bala et al. discloses all of the limitations as previously discussed with respect to claim 11 including that wherein the processing circuitry is configured to compare a value or range of a quantified physical characteristic to a historical value or range (Munoz: paragraphs [0090], [0107], and [0110]; paragraph [0164] – as more information is gathered as a spectral library is compiled and techniques are refined and such information can be evaluated with deep learning and computer learning to investigate patterns and derive statistical significance between specific patterns and clinical information – the system has the capability to become a diagnostic device as it relates to tissue pathology, tissue healing and tissue regeneration).
Regarding claim 15, Munoz in view of Bala et al. discloses all of the limitations as previously discussed with respect to claims 11 and 14 including that wherein the value or range of the quantified physical characteristic is of biological tissue associated with injuries or ailments (Munoz: paragraphs [0011], [0089], [0101], and [0110]; paragraph [0056] – embodiments of the present invention provide a three dimensional reconstruction of visual and anatomical data and augmentation of color spectral patterns that serve as spectral fingerprints of distinct tissue types and characteristics acquired from an area of interest, which facilitates an early evaluation of tissue pathology (e.g., malignancies, ulcers, eschars, scabs, wounds, etc.) and tissue healing and regeneration in, for example, wounds, thereby providing early disease detection, promoting earlier interventions and reducing the number of complications with tissue pathologies and the number of advanced interventions that result from wound complications and other tissue pathologies; paragraph [0164] – as more information is gathered as a spectral library is compiled and techniques are refined and such information can be evaluated with deep learning and computer learning to investigate patterns and derive statistical significance between specific patterns and clinical information – the system has the capability to become a diagnostic device as it relates to tissue pathology, tissue healing and tissue regeneration).
Regarding claim 16, Munoz discloses a method of assessing a medical condition of a patient using a mobile imaging system (Figs. 2 and 10), comprising: configuring processing circuitry of a mobile phone to capture images from a camera system including a smartphone camera integrated into the mobile phone (Fig. 10 – mobile phone; paragraph [0132] – the portable device of Fig. 10 includes a hyperspectral imager 110 and a camera 140 (e.g., a visible, and IR imager) – in a particular embodiment, a fisheye camera 140 of a mobile device 50 takes a RGB image of the region of interest, an IR camera 140 takes a laser speckle image of the region of interest, and a hyperspectral camera 110 takes a hyperspectral image of the region of interest); which is configured for taking images using the smartphone camera at a predetermined range of wavelengths including visible, near-infrared, and infrared wavelengths (Fig. 9 – infrared; paragraph [0079] – infrared; paragraph [0082] - visible and near-infrared); and an infrared camera configured to capture images in an infrared light spectrum (Fig. 10 – mobile phone; paragraph [0132] – the portable device of Fig. 10 includes a hyperspectral imager 110 and a camera 140 (e.g., a visible, and IR imager) – in a particular embodiment, a fisheye camera 140 of a mobile device 50 takes a RGB image of the region of interest, an IR camera 140 takes a laser speckle image of the region of interest, and a hyperspectral camera 110 takes a hyperspectral image of the region of interest); collecting multispectral imaging data of biological tissue of the patient, wherein the multispectral imaging data includes at least the plurality of near-infrared and infrared images (paragraphs [0030], [0034], [0036], and [0038] - the computer analytics program can perform the aggregation of image data…synthesis of image data reports for clinical care, patient and clinical meta-data, direct and/or indirect interface with healthcare related software programs and portals, clinical meta-data reports, statistical modeling, and machine learning capabilities…acquiring the raw laser speckle image and hyperspectral image and 3D surface image of a tissue region of interest of a subject in need thereof; and analyze and monitor the tissue region of interest, and optionally diagnosing, triaging, intervening, and/or treating the subject having tissue pathology); and quantifying a physical characteristic of the biological tissue including at least one of tissue edema or swelling, tissue oxygenation, tissue perfusion, bacterial load, bioburden, a wound area, or a wound volume (paragraphs [0011], [0089], [0101], and [0110]; paragraph [0056] – embodiments of the present invention provide a three dimensional reconstruction of visual and anatomical data and augmentation of color spectral patterns that serve as spectral fingerprints of distinct tissue types and characteristics acquired from an area of interest, which facilitates an early evaluation of tissue pathology (e.g., malignancies, ulcers, eschars, scabs, wounds, etc.) and tissue healing and regeneration in, for example, wounds, thereby providing early disease detection, promoting earlier interventions and reducing the number of complications with tissue pathologies and the number of advanced interventions that result from wound complications and other tissue pathologies; paragraph [0164] – as more information is gathered as a spectral library is compiled and techniques are refined and such information can be evaluated with deep learning and computer learning to investigate patterns and derive statistical significance between specific patterns and clinical information – the system has the capability to become a diagnostic device as it relates to tissue pathology, tissue healing and tissue regeneration). However, Munoz fails to disclose a movable filter assembly including a plurality of optical filters each selectively positionable with respect to the smartphone camera, the near-infrared images to be captured using the smartphone camera and an optical filter selected from the plurality of optical filters.
Referring to the Bala et al. reference, Bala et al. discloses a mobile imaging method, comprising: a movable filter assembly including a plurality of optical filters each selectively positionable with respect to the smartphone camera (Bala et al.: Figs. 9 and 10; paragraph [0040] – a mobile hyperspectral camera system that is built into a standard consumer device such as a smartphone or tablet can offer many beneficial applications to a consumer – for example, an image of a person’s face captured under near infra-red (NIR) illumination produces smooth pleasing skin tones, and can thus be combined with RGB images to enhance selfie images – combining NIR and RGB images can also offer improved biometrics capabilities – facial images taken under ultra-violet (UV) light reveal useful features indicative of skin health and aging – incorporating such technologies into a common consumer mobile device such as a smartphone enables a rich suite of applications that can combine the power of hyperspectral imaging with contextual knowledge already available on the device, such as the user’s environment, lifestyle, and activities; paragraph [0049] – Fig. 9, a diagram shows a sleeve used for a mobile device implementing a hyperspectral camera system having multiple cameras on a rear side, wherein the inside portion of the sleeve of Fig. 9 is shown in Fig. 10 – as shown in Fig. 9, a sleeve 902, also commonly known as a cover or case, attachable to the device 200, containing a rotating wheel may be placed over the camera 302 and an opening 904 is provided for the flash array 304 – more particularly, a rotating filter wheel 906 comprises a plurality of filters 908, each of which may be aligned with the lens of the camera – by providing a movable wheel as shown, different filters may be selected without having to physically remove and replace a filter attachment for the device – a second aperture 914 is provided for the lens of the camera 303 – camera 303 may be an RGB camera, while the camera 302 will be determined based upon the selected filter of the filter wheel 906), the near-infrared images to be captured using the smartphone camera and an optical filter selected from the plurality of optical filters (Bala et al.: Figs. 9 and 10; paragraph [0040] – a mobile hyperspectral camera system that is built into a standard consumer device such as a smartphone or tablet can offer many beneficial applications to a consumer – for example, an image of a person’s face captured under near infra-red (NIR) illumination produces smooth pleasing skin tones, and can thus be combined with RGB images to enhance selfie images – combining NIR and RGB images can also offer improved biometrics capabilities – facial images taken under ultra-violet (UV) light reveal useful features indicative of skin health and aging – incorporating such technologies into a common consumer mobile device such as a smartphone enables a rich suite of applications that can combine the power of hyperspectral imaging with contextual knowledge already available on the device, such as the user’s environment, lifestyle, and activities; paragraph [0049] – Fig. 9, a diagram shows a sleeve used for a mobile device implementing a hyperspectral camera system having multiple cameras on a rear side, wherein the inside portion of the sleeve of Fig. 9 is shown in Fig. 10 – as shown in Fig. 9, a sleeve 902, also commonly known as a cover or case, attachable to the device 200, containing a rotating wheel may be placed over the camera 302 and an opening 904 is provided for the flash array 304 – more particularly, a rotating filter wheel 906 comprises a plurality of filters 908, each of which may be aligned with the lens of the camera – by providing a movable wheel as shown, different filters may be selected without having to physically remove and replace a filter attachment for the device – a second aperture 914 is provided for the lens of the camera 303 – camera 303 may be an RGB camera, while the camera 302 will be determined based upon the selected filter of the filter wheel 906).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have had included a filter assembly configured to movably position a plurality of optical filters with respect to the smartphone camera as disclosed by Bala et al. in the system disclosed by Munoz in order to enhance the smartphone camera that is integrated into the smartphone and to allow the user to select the appropriate filter thereby providing a robust, cost-effective non-invasive and rapid imaging-based method or device for collecting data.
Regarding claim 17, Munoz in view of Bala et al. discloses all of the limitations as previously discussed with respect to claim 16 including that wherein the collecting multispectral imaging data includes sequentially positioning at least two optical filters selected from the plurality of optical filters in a position proximal to the smartphone camera (Munoz: Fig. 10; paragraph [0082]; Bala et al.: Figs. 9 and 10; paragraph [0040] – a mobile hyperspectral camera system that is built into a standard consumer device such as a smartphone or tablet can offer many beneficial applications to a consumer – for example, an image of a person’s face captured under near infra-red (NIR) illumination produces smooth pleasing skin tones, and can thus be combined with RGB images to enhance selfie images – combining NIR and RGB images can also offer improved biometrics capabilities – facial images taken under ultra-violet (UV) light reveal useful features indicative of skin health and aging – incorporating such technologies into a common consumer mobile device such as a smartphone enables a rich suite of applications that can combine the power of hyperspectral imaging with contextual knowledge already available on the device, such as the user’s environment, lifestyle, and activities; paragraph [0049] – Fig. 9, a diagram shows a sleeve used for a mobile device implementing a hyperspectral camera system having multiple cameras on a rear side, wherein the inside portion of the sleeve of Fig. 9 is shown in Fig. 10 – as shown in Fig. 9, a sleeve 902, also commonly known as a cover or case, attachable to the device 200, containing a rotating wheel may be placed over the camera 302 and an opening 904 is provided for the flash array 304 – more particularly, a rotating filter wheel 906 comprises a plurality of filters 908, each of which may be aligned with the lens of the camera – by providing a movable wheel as shown, different filters may be selected without having to physically remove and replace a filter attachment for the device – a second aperture 914 is provided for the lens of the camera 303 – camera 303 may be an RGB camera, while the camera 302 will be determined based upon the selected filter of the filter wheel 906).
Regarding claim 18, Munoz in view of Bala et al. discloses all of the limitations as previously discussed with respect to claims 1 and 16 including that wherein the illumination module is configured to sequentially emit light in at least three different wavelengths, and wherein the filter assembly includes at least three optical filters each configured for use during emission of one of the at least three different wavelengths of light that the illumination module is configured to emit (Munoz: paragraphs [0068]-[0073] and [0160]).
Regarding claim 20, Munoz in view of Bala et al. discloses all of the limitations as previously discussed with respect to claim 16 including that the method further comprises classifying an injury or ailment by comparing, using the processing circuitry, a value or range of the quantified physical characteristic to a library of threshold values or ranges (Munoz: paragraphs [0090], [0107], and [0110]; paragraph [0164] – as more information is gathered as a spectral library is compiled and techniques are refined and such information can be evaluated with deep learning and computer learning to investigate patterns and derive statistical significance between specific patterns and clinical information – the system has the capability to become a diagnostic device as it relates to tissue pathology, tissue healing and tissue regeneration).
Regarding claim 21, Munoz in view of Bala et al. discloses all of the limitations as previously discussed with respect to claim 16 including that the method further comprises tracking a change in an injury or ailment by comparing, using the processing circuitry, a value or range of the quantified physical characteristic to a historical value or range obtained by quantifying the physical characteristic of the biological tissue associated with the injury or ailment during at least one former point in time (Munoz: paragraphs [0090], [0107], and [0110]; paragraph [0164] – as more information is gathered as a spectral library is compiled and techniques are refined and such information can be evaluated with deep learning and computer learning to investigate patterns and derive statistical significance between specific patterns and clinical information – the system has the capability to become a diagnostic device as it relates to tissue pathology, tissue healing and tissue regeneration; paragraphs [0133] and [0135] – analyzing the tissue region of interest 530, and optionally, documenting, reporting, tracking, diagnosing and/or treating the tissue pathology of the subject).
Regarding claim 22, Munoz in view of Bala et al. discloses all of the limitations as previously discussed with respect to claim 16 including that the method further comprises comparing, using the processing circuitry, a value or range of the quantified physical characteristic to a historical value or range obtained by quantifying the physical characteristic of biological tissue associated with an injury or ailment of other patients (Munoz: paragraphs [0011], [0038], [0089], [0101], [0110], and [0135]; paragraph [0056] – embodiments of the present invention provide a three dimensional reconstruction of visual and anatomical data and augmentation of color spectral patterns that serve as spectral fingerprints of distinct tissue types and characteristics acquired from an area of interest, which facilitates an early evaluation of tissue pathology (e.g., malignancies, ulcers, eschars, scabs, wounds, etc.) and tissue healing and regeneration in, for example, wounds, thereby providing early disease detection, promoting earlier interventions and reducing the number of complications with tissue pathologies and the number of advanced interventions that result from wound complications and other tissue pathologies; paragraph [0164] – as more information is gathered as a spectral library is compiled and techniques are refined and such information can be evaluated with deep learning and computer learning to investigate patterns and derive statistical significance between specific patterns and clinical information – the system has the capability to become a diagnostic device as it relates to tissue pathology, tissue healing and tissue regeneration).
Claim 19 is rejected under 35 U.S.C. 103 as being unpatentable over Munoz in view of Bala et al. as applied to claim 16 above, and further in view of Dacosta (U.S. Patent Application Publication 2020/0104998).
Regarding claim 19, Munoz in view of Bala et al. discloses all of the limitations as previously discussed with respect to claim 16, but fails to disclose that the method further comprises introducing fluorescent dye to the patient, and wherein the collecting the multispectral imaging data includes collecting multispectral fluorescence imaging data.
Referring to the Dacosta reference, Dacosta discloses a mobile imaging method, comprising: introducing fluorescent dye to the patient, and wherein the collecting the multispectral imaging data includes collecting multispectral fluorescence imaging data (Dacosta: paragraphs [0068], [0135], and [0154] – the target object 10 may be marked with a mark 11 to allow for multiple images to be taken of the object and then being co-registered for analysis - the mark 11 may involve, for example, the use of exogenous fluorescence dyes of different colors which may produce multiple distinct optical signals when illuminated by the light sources 5 and be detectable within the image of the object 10 and thus may permit orientation of multiple images (e.g., taken over time) of the same region of interest by co-registering the different colors and the distances between them).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to have had introduced fluorescent dye to the patient, and wherein the collecting the multispectral imaging data includes collecting multispectral fluorescence imaging data as disclosed by Dacosta in the method disclosed by Munoz in view of Bala et al. in order to gain more information about the patient.
Conclusion
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/HEATHER R JONES/Primary Examiner, Art Unit 2481
May 14, 2026
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