US 11,893,729 B2
Multi-modal computer-aided diagnosis systems and methods for prostate cancer
Adele Courot, Buc (FR); Nicolas Gogin, Buc (FR); Baptiste Perrin, Buc (FR); Lorraine Jammes, Buc (FR); Lucile Nosjean, Buc (FR); and Melodie Sperandio, Buc (FR)
Assigned to GE Precision Healthcare LLC, Wauwatosa, WI (US)
Filed by GE Precision Healthcare LLC, Wauwatosa, WI (US)
Filed on Sep. 3, 2020, as Appl. No. 17/011,778.
Application 17/011,778 is a continuation in part of application No. 16/196,887, filed on Nov. 20, 2018, granted, now 11,069,056.
Claims priority of provisional application 62/590,266, filed on Nov. 22, 2017.
Prior Publication US 2020/0402236 A1, Dec. 24, 2020
Int. Cl. G06T 7/00 (2017.01); G06N 3/02 (2006.01); G16H 30/40 (2018.01); G06T 7/62 (2017.01); A61B 5/00 (2006.01); G16H 50/20 (2018.01); A61B 8/08 (2006.01); G16H 10/60 (2018.01); G16H 40/20 (2018.01); A61B 6/03 (2006.01); A61B 5/055 (2006.01)
CPC G06T 7/0012 (2013.01) [A61B 5/4381 (2013.01); G06T 7/62 (2017.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); A61B 5/055 (2013.01); A61B 6/032 (2013.01); A61B 6/037 (2013.01); A61B 8/085 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30081 (2013.01); G06T 2207/30096 (2013.01); G16H 10/60 (2018.01); G16H 40/20 (2018.01)] 10 Claims
OG exemplary drawing
 
1. An apparatus for providing a prostate condition diagnosis comprising:
a memory to store instructions; and
a processor to execute the instructions to:
detect, using a neural network, a lesion from an image of a prostate gland based at least in part on a prostate mask comprising one or more zones of the prostate gland;
generate a mapping of the lesion from the image to a sector map without user input, the generating the mapping of the lesion comprising identifying a depth region of the lesion, wherein the depth region indicates a location of the lesion along a depth axis, wherein the processor is to generate the mapping of the lesion by using a digital twin; and
provide the sector map comprising a representation of the lesion within the prostate gland mapped from the image to the sector map, and wherein the processor is to generate a score using the neural network and the provided sector map comprising the representation of the lesion mapped from the image to the sector map,
wherein the depth region is identified using an apex region, a mid region, and a base region of the prostate gland,
wherein the generating the mapping comprises calculating one or more polar coordinates relative to a center of the lesion in the image,
wherein the generating the mapping comprises computing a normalized radius based on the center of the lesion in the image, and
wherein the generating the mapping comprises computing a de-normalized radius based on the normalized radius and one or more dimensions of the sector map.