US 12,444,050 B2
Machine learning systems and methods for assessment, healing prediction, and treatment of wounds
Wensheng Fan, Plano, TX (US); John Michael DiMaio, Dallas, TX (US); Jeffrey E. Thatcher, Irving, TX (US); Peiran Quan, Dallas, TX (US); Faliu Yi, Allen, TX (US); Kevin Plant, Dallas, TX (US); Ronald Baxter, Grand Prairie, TX (US); Brian McCall, Dallas, TX (US); Zhicun Gao, Plano, TX (US); and Jason Dwight, Dallas, TX (US)
Assigned to Spectral MD, Inc., Dallas, TX (US)
Filed by SPECTRAL MD, INC., Dallas, TX (US)
Filed on Mar. 28, 2024, as Appl. No. 18/620,830.
Application 18/620,830 is a continuation of application No. 18/177,493, filed on Mar. 2, 2023, granted, now 11,948,300.
Application 18/177,493 is a continuation of application No. 17/013,336, filed on Sep. 4, 2020, granted, now 11,599,998, issued on Mar. 7, 2023.
Application 17/013,336 is a continuation of application No. 16/738,911, filed on Jan. 9, 2020, granted, now 10,783,632, issued on Sep. 22, 2020.
Application 16/738,911 is a continuation of application No. PCT/US2019/065820, filed on Dec. 11, 2019.
Claims priority of provisional application 62/818,375, filed on Mar. 14, 2019.
Claims priority of provisional application 62/780,854, filed on Dec. 17, 2018.
Claims priority of provisional application 62/780,121, filed on Dec. 14, 2018.
Prior Publication US 2024/0281966 A1, Aug. 22, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06T 7/00 (2017.01); A61B 5/00 (2006.01); G06T 7/11 (2017.01); G16H 30/40 (2018.01); G16H 50/30 (2018.01)
CPC G06T 7/0012 (2013.01) [A61B 5/445 (2013.01); A61B 5/7275 (2013.01); G06T 7/11 (2017.01); G16H 30/40 (2018.01); G16H 50/30 (2018.01); A61B 5/0077 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30088 (2013.01); G06T 2207/30096 (2013.01)] 25 Claims
OG exemplary drawing
 
1. A system for assessing or predicting wound healing, the system comprising:
an application executable by a mobile computing device, the mobile computing device comprising one or more processors in communication with at least one light detection element, the one or more processors configured with processor-executable instructions included in the application to perform operations comprising:
receiving at least one signal from the light detection element representing light of at least a first wavelength reflected from a tissue region comprising a wound or portion thereof;
generating, based on the at least one signal, an image having a plurality of pixels depicting the tissue region;
determining, based on the signal, a reflectance intensity value at the first wavelength for each pixel of at least a subset of the plurality of pixels;
determining one or more quantitative features of the subset of the plurality of pixels based on the reflectance intensity values of each pixel of the subset; and
causing generation, using one or more machine learning algorithms, of at least one scalar value based on the one or more quantitative features of the subset of the plurality of pixels, the at least one scalar value corresponding to a predicted amount of healing of the wound or portion thereof over a predetermined time interval following generation of the image.