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 .
Prior arts cited in this office action:
Sarvazyan (US 20250221614 A1, hereinafter “Sarvazyan”)
Park et al. (KR 20230064693 A, hereinafter “Park”)
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, 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Sarvazyan (US 20250221614 A1, hereinafter “Sarvazyan”) and in view of Park et al. (KR 20230064693 A, hereinafter “Park”).
Regarding claims 1, 13 and 20:
Sarvazyan teaches an electronic device configured to, based on a hyperspectral image
sensor, analyze biological tissue (Sarvazyan [0002]-[0003], [0025], [0029] where Sarvazyan teaches hyperspectral imaging (HSI) is a technology that captures spectral information across multiple wavelengths from each pixel of an image. That information facilitates the identification and classification of objects, materials, or areas of an image based on their spectral properties. Contrary to conventional color imaging systems that record intensity from red, green, and blue bands, HSI creates an extensive array of nearly contiguous spectrum, thereby enabling the detection and categorization of small differences in spectral properties of the target, including object's diffuse reflection, absorption or autofluorescence. One limitation of HSI is that in its current form it collects only a small subset of useful spectral information. This provides much more spectral information to enable better identification and characterization of different tissue types, materials, etc. ), the electronic device comprising:
at least one light source configured to emit light at a plurality of angles of incidence with respect to a biological tissue region being measured (Sarvazyan [0011], [0020], [0029]-[0030], fig. 2(a), where Sarvazyan teaches an alternative to having an additional optical path 2, a filter 208 can be inserted after of light source 201a to illuminate the sample with different excitation wavelengths);
a hyperspectral image sensor configured to acquire a plurality of reflection signals corresponding to the light that is emitted at the plurality of angles of incidence from the at least one light source and is reflected from the biological tissue region being measured (Sarvazyan [0011], [0020], [0029]-[0030], fig. 2(a), and figure 3, where Sarvazyan teaches An alternative to having an additional optical path 2, a filter 208 can be inserted after of light source 201a to illuminate the sample with different excitation wavelengths);
and
at least one processor electrically connected to the at least one light source and
the hyperspectral image sensor (Sarvazyan [0087], where Sarvazyan teaches It is further noted that the processing device 401 can be implemented by a computer or computing device having a processor or controller to perform various functions and operations in accordance with the disclosure. The processing device can be, for instance, a personal computer (PC), server or mainframe computer, or be based on cloud computing. The processing device may also be provided with one or more of a wide variety of components or subsystems including, for example, a co-processor, register, data processing devices and subsystems, wired or wireless communication links, input devices, monitors, memory or storage devices such as a database), wherein the at least one processor is configured to:
generate a plurality of hyperspectral images based on the plurality of
reflection signals acquired through the hyperspectral image sensor (Sarvazyan [0011], [0020], [0029]-[0030], fig. 2(a), and figure 3, where a plurality of images are generated);
measure reflectance changes based on the plurality of angles of incidence, from the generated plurality of hyperspectral images (Sarvazyan [0010], [0028],claims 12 and 13, where Sarvazyan teaches FIGS. 2(a), (b), (c) show diagrams of HE-HSI systems for fast acquisition of reflectance and fluorescence spectra using snapshot hyperspectral cameras which acquire multiple spectral planes simultaneously); and
generate biological tissue analysis data, based on the measured reflectance changes (Sarvazyan [0010],[0025], [0072]).
Sarvazyan fails to explicitly teaches if the biological tissue is skin tissue
However, Park teaches As shown in FIG. 1, the hyperspectral skin image depth analysis apparatus according to an embodiment of the present invention includes a hyperspectral imaging apparatus 100 for imaging a region including a burned skin part in a living body such as a human; A hyperspectral analyzer 200 that calculates analysis data using spectral reflectance and spectral image data obtained by photographing, and a display device 300 that displays an analysis image using the calculated analysis data, The analysis data is a modified skin image spectral index (mSBSI: modified Skin Burns Spectral Index). Here, the hyperspectral imaging apparatus 100 is composed of a hyperspectral camera, a halogen light source for illuminating an object, and a reflector, as shown in FIG. 2 (Park [0042]-[0046]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the application to configured the system such that it is based on a hyperspectral image sensor, to analyze biological tissue such as biological skin, in order to diagnosing skin diseases or skin cancer through measurement.
Regarding claims 2 and 14:
Sarvazyan in view Park teaches wherein the at least one processor is further configured to generate, based on the measured reflectance changes, the skin analysis data comprising at least one of thickness of skin tissue, melanin concentration in skin tissue, moisture content, blood volume, hemoglobin concentration in blood, tumor size, and tumor location (Sarvazyan [0072]; Park [0005]).
Regarding claims 3:
Sarvazyan in view Park teaches wherein the at least one light source comprising a plurality of light sources respectively configured to emit the light at the plurality of angles of incidence with respect to the skin region being measured (Sarvazyan [0011], [0020], [0029]-[0030], fig. 2(a); Park claim 6)
Regarding claim 4:
Sarvazyan in view Park teaches wherein the at least one light source comprises one light source configured to rotate to emit the light at the plurality of angles of incidence with respect to the skin region being measured (Sarvazyan [0020], [0032]).
Regarding claims 5 and 15:
Sarvazyan in view Park teaches wherein the hyperspectral image sensor is further configured to acquire the plurality of reflection signals based on a snapshot method of dividing into a plurality of spectral regions and simultaneously measuring the plurality of spectral regions (Sarvazyan [0011], [0020], [0029]-[0032], fig. 2(a); Park [0042], claim 6).
Regarding claims 6 and 16:
Sarvazyan in view Park teaches wherein the at least one processor, through the hyperspectral image sensor, is further configured to:
acquire a first plurality of reflection signals of light that is emitted from the at
least one first light source configured to emit light at a first angle of incidence and is
reflected from the skin region being measured; and
acquire, after the first plurality of reflection signals are acquired, a second
plurality of reflection signals of light that is emitted from at least one second light source
configured to emit light at a second angle of incidence different from the first angle of
incidence and is reflected from the skin region being measured (Sarvazyan [0011], [0020], [0029]-[0032], fig. 2(a), figs. 1-3; Park [0042], claim 6).
Regarding claims 7 and 17:
Sarvazyan in view Park teaches wherein the hyperspectral image sensor is further configured to acquire the plurality of reflection signals based on a line scanning method in which measuring is performed through a single line sensor while moving along a y-axis (Sarvazyan [0035], [0042], [0049] figs. 1-3; Park [0048]-[0049]).
Regarding claims 8 and 18:
Sarvazyan in view Park teaches wherein the at least one processor, by the hyperspectral image sensor at a first position, is further configured to:
acquire a plurality of reflection signals of light that is emitted from at least one first light source configured to emit light at a first angle of incidence and at least one second light source configured to emit light at a second angle of incidence different from the first angle of incidence and is reflected from the skin region being measured;
and
acquire, based on the hyperspectral image sensor being at a second position different from the first position, a plurality of reflection signals of light that is emitted from the at least one first light source and the at least one second light source and is reflected from the skin region being measured (Sarvazyan [0035], [0042], [0049] figs. 1-3; Park [0048]-[0049]).
Regarding claims 9 and 19:
Sarvazyan in view Park teaches wherein the at least one processor, through the hyperspectral image sensor arranged to be movable from a first position to a second position, is further configured to:
acquire a plurality of reflection signals of light that is emitted from the at least
one first light source configured to emit light at a first angle of incidence and is reflected
from the skin region being measured, by moving the hyperspectral image sensor from
the first position to the second position; and
acquire a plurality of reflection signals of light that is emitted from the at least
one second light source configured to emit light at a second angle of incidence different
from the first angle of incidence and is reflected from the skin region being measured,
by moving the hyperspectral image sensor from the first position to the second
position (Sarvazyan [0035], [0042], [0049] figs. 1-3; Park [0048]-[0049]).
Regarding claim 10:
Sarvazyan in view Park teaches wherein a wavelength band of the at least one light source and the hyperspectral image sensor is in a range of 450 nm to 2500 nm (Sarvazyan [0035], [0042], [0049] figs. 1-3; Park [0048]-[0049]).
Regarding claim 11:
Sarvazyan in view Park teaches wherein a wavelength band of the at least one light source and the hyperspectral image sensor is in a range of 450 nm to 1100 nm (Sarvazyan [0035], [0042], [0049] figs. 1-3; Park [0048]-[0049]).
Regarding claim 12:
Sarvazyan in view Park teaches further comprising a display, wherein the at least one processor is further configured to output the generated skin analysis data through the display (Park [0048], [0059], [0063]; Park [0048]-[0049]).
Conclusion
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/WEDNEL CADEAU/Primary Examiner, Art Unit 2632 August 11, 2026
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