| CPC G06T 7/0012 (2013.01) [G06V 20/698 (2022.01); G16H 15/00 (2018.01); G16H 30/40 (2018.01); G06T 2207/30024 (2013.01); G06T 2207/30096 (2013.01); G06T 2207/30168 (2013.01); G06T 2207/30204 (2013.01); G06V 2201/03 (2022.01)] | 17 Claims |
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1. A computing device comprising:
at least one memory; and
at least one processor configured to:
use a machine learning model to detect a plurality of tissue regions and cancer region from a pathological slide image,
generate quantitative information about the detected tissue regions and cancer region,
compare the quantitative information with a predetermined reference value, wherein the quantitative information comprises an area corresponding to entire tissue regions and an area corresponding to the cancer region,
determine whether the pathological slide image has passed a quality evaluation test based on a comparison between the quantitative information with the predetermined reference value, such that a result of the quality evaluation test is used in determining whether to perform downstream analysis on the pathological slide image, and
display on a display device the result of the quality evaluation test indicating whether the pathological slide image has passed the quality evaluation test,
wherein the processor determines that the pathological slide image has failed the quality evaluation test if the area corresponding to entire tissue regions is smaller than a first reference value or the area corresponding to the cancer region is smaller than a second reference value.
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