| CPC G06T 7/0012 (2013.01) [G06F 18/2148 (2023.01); G06F 18/2431 (2023.01); G06N 3/08 (2013.01); G06V 10/449 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 20/698 (2022.01); G06T 2207/20076 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01)] | 20 Claims |

|
1. An image analysis method comprising:
inputting analysis data into a deep learning algorithm having a neural network structure, the analysis data being generated from an image of an analysis target cell and including information regarding the analysis target cell; and
classifying, by use of the deep learning algorithm, the analysis target cell into at least one of categories of a blood cell, wherein
the categories include morphological features of white blood cells observed in myelodysplastic syndromes, wherein
the morphological features of white blood cells include at least morphological nucleus abnormality, presence of vacuole, granule morphological abnormality, granule distribution abnormality, presence of abnormal granule, cell size abnormality, presence of inclusion body, or bare nucleus.
|