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 Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1 and 12-14 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Stumpe et al. (US Patent Pub. No. 2021/0018742 A1, published January 2021).
Regarding claim 1, Stumpe teaches a classification apparatus comprising: an imaging section for capturing an image which includes a partial range of a pathological sample as a subject (Fig. 2B), and at least one processor, the at least one processor carrying out: an acquisition process of acquiring the image which has been captured by the imaging section (Para. 56, “The compute unit further includes various interfaces to other components of the system including an interface, not shown, to receive the digital images from the camera”); and a classification process of classifying, as benign or malignant, a cell included as a subject in the image which has been acquired in the acquisition process (Para. 15, “the compute unit implements one or more machine learning pattern recognizers trained to identify individual tumor cells or areas of tumor cells which are classified in accordance with specific Gleason grade”).
Regarding claim 12, the recited method performs variably the same function as that of claim 1. It is rejected under the same analysis.
Regarding claim 13, the recited non-transitory storage medium (Para. 116, “While SD cards are illustrated in FIG. 9, other physical formats of memory devices capable of storing machine learning pattern recognition models could of course be used”) performs variably the same function as that of claim 1. It is rejected under the same analysis.
Regarding claim 14, Stumpe teaches all of the elements of claim 1, as stated above, as well as in the classification process, a machine learning model which has been optimized is used (Para. 15, “the compute unit implements one or more machine learning pattern recognizers trained to identify individual tumor cells or areas of tumor cells which are classified in accordance with specific Gleason grade”).
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.
Claim(s) 9-11 are rejected under 35 U.S.C. 103 as being unpatentable over Stumpe.
Regarding claim 9, Stumpe teaches that a drive process of moving an imaging range of the imaging section is carried out (Para. 45, “enables the system 100 of FIG. 1 to continue to provide enhancements to the field of view and assist the pathologist in characterizing or classifying the specimen in substantial real time as the operator navigates around the slide (e.g., by use of a motor 116 driving the stage), by changing magnification by switching to a different objective lens 108A or 108B”); the at least one processor further carries out an adjustment process of adjusting an imaging magnification of the imaging section (Para. 45 above); the at least one processor further carries out a reception process of receiving an instruction from a user (Para. 81, “By using the mouse 146 or keyboard 144 the pathologist could enter commands on the workstation to cause the microscope stage motor 116 to step through a sequence of positions on the slide containing areas of interest. ”); and the at least one processor further carries out a control process of adjusting, in the adjustment process, the imaging magnification to a first magnification or to a second magnification which is higher than the first magnification, and causing, in the drive means, the imaging range to move in accordance with the instruction from the user received in the reception process (Para. 45 above, changing magnification between two lenses necessarily adjusts between a first and second magnification, and having the second be higher than the first would have been obvious to one of ordinary skill in the art).
Stumpe does not explicitly disclose that the processor carries out a drive process.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Stumpe to include that the processor carries out a drive process of moving an imaging range of the imaging section. Stumpe discloses the use of a motor which allows an operator to perform a drive operation. One of ordinary skill in the art would have understood that having an automated drive process is well-known in the art (See Bueno in Pertinent Prior Art) and enhancing the already disclosed drive method of Stumpe to an automated system would have been an obvious design choice, predictably increasing its proficiency at assisting pathologists in classifying samples.
Regarding claim 10, Stumpe teaches all of the elements of claim 9, as stated above, as well as wherein: in a case where in the reception process, the at least one processor has not received, for a predetermined time period, an instruction to cause the imaging range to move in the drive process, the at least one processor carries out, in the control process, an automatic classification process in which the at least one processor adjusts, in the adjustment process, the imaging magnification to the second magnification which is higher than the first magnification, the at least one processor acquires, in the acquisition process, a second image at the second magnification (Para. 45, “enables the system 100 of FIG. 1 to continue to provide enhancements to the field of view and assist the pathologist in characterizing or classifying the specimen in substantial real time as the operator navigates around the slide (e.g., by use of a motor 116 driving the stage), by changing magnification by switching to a different objective lens 108A or 108B”, setting this magnification to occur after a specific time period where no movement has occurred would have been a predictable variation to one of ordinary skill in the art), and the at least one processor classifies, as benign or malignant, a cell which is included as a subject in the second image in the classification process (Para. 15, “the compute unit implements one or more machine learning pattern recognizers trained to identify individual tumor cells or areas of tumor cells which are classified in accordance with specific Gleason grade”).
Regarding claim 11, Stumpe as modified teaches all of the elements of claim 9, as stated above, as well as wherein: in a case where the at least one processor has received, in the reception process, an instruction to adjust, in the adjustment process, the imaging magnification to a second magnification which is higher than the first magnification, in the control process, the at least one processor acquires, in the acquisition process, a second image at the second magnification (Para. 45 above), and classifies, as benign or malignant, a cell which is included as a subject in the second image in the classification process (Para. 15 above).
Allowable Subject Matter
Claims 2-8 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
Pertinent Prior Art: Bueno, G., Déniz, O., Fernández-Carrobles, M. D. M., Vállez, N., & Salido, J. (2014). An automated system for whole microscopic image acquisition and analysis. Microscopy Research and Technique, 77(9), 697–713. https://doi.org/10.1002/jemt.22391 Provides an automated system for microscopic imagery with multiple magnification levels. Does not count cells for further analysis.
Alegro, M., Castruita, P. A., Seeley, W. W., Heinsen, H., Ushizima, D., Grinberg, L. T., Theofilas, P., & Nguy, A. (2017). Automating cell detection and classification in human brain fluorescent microscopy images using dictionary learning and sparse coding. Journal of Neuroscience Methods, 282, 20–33. https://doi.org/10.1016/j.jneumeth.2017.03.002 Performs automatic cell detection, counting, and classification using a dictionary.
Molecular Devices. (2019). ImageXpress Pico Automated Cell Imaging System. https://www.moleculardevices.com/sites/default/files/en/assets/brochures/dd/img/imagexpress-pico-automated-cell-imaging-system.pdf State of the art automated cell imaging system with cell counting, different magnification levels, and a drive motor. Does not adjust magnification levels based on a cell count.
Zeder, M., Kohler, E., & Pernthaler, J. (2009). Automated quality assessment of autonomously acquired microscopic images of fluorescently stained bacteria. Cytometry Part A, 9999A, NA-NA. https://doi.org/10.1002/cyto.a.20810 Talks about the difficulty of autonomously imaging cells, citing problems such as images with no cells, too high cell densities, or bad distribution of cells in the captured images, indicating the importance of cell count in a microscopic image for analysis.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAVID A WAMBST whose telephone number is (703)756-1750. The examiner can normally be reached M-F 9-6:30 EST.
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/DAVID ALEXANDER WAMBST/Examiner, Art Unit 2663
/GREGORY A MORSE/Supervisory Patent Examiner, Art Unit 2698
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