US 12,462,395 B2
Simulating progression of skin conditions based on machine learning
Yuan Yuan Ding, Shanghai (CN); Yi Chen Zhong, Shanghai (CN); Jing Zhang, Shanghai (CN); Yang Liu, Zhong Xin (CN); Ziyi Jiang, Shanghai (CN); and Ting Ting Cao, Beijing (CN)
Assigned to International Business Machines Corporation, Armonk, NY (US)
Filed by International Business Machines Corporation, Armonk, NY (US)
Filed on Dec. 13, 2022, as Appl. No. 18/065,207.
Prior Publication US 2024/0193787 A1, Jun. 13, 2024
Int. Cl. G06T 7/136 (2017.01); G06T 5/70 (2024.01)
CPC G06T 7/136 (2017.01) [G06T 5/70 (2024.01); G06T 2207/10024 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30088 (2013.01); G06T 2207/30201 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method of skin-condition visualization, the computer-implemented method comprising:
retrieving a color image depicting facial skin of a subject;
generating a monochromatic version of the color image;
segmenting, based on a segmentation threshold and using a machine learning model, a plurality of candidate instances of one or more skin conditions from the monochromatic version;
generating a polarized version of the color image, wherein based on the polarized version, the plurality of candidate instances is filtered to exclude at least one candidate instance such that one or more candidate instances remain as one or more finalized instances; and
generating, based on the one or more finalized instances and by operation of one or more computer processors, one or more simulation images that simulate an improving or worsening of the one or more finalized instances over time relative to the color image.