System and method for determining high-temperature region pixels on a mammography image

A method for annotating mammography images of a subject using thermal images and mammography images of the subject by determining a block of pixels on the mammography images corresponding to high temperature regions on the thermal images of the subject comprising,

• capturing a thermal image of the subject using a thermal imaging device;
• capturing the mammography image of the subject using a mammography imaging device;
• identifying a first breast region in the thermal image of the subject;
• identifying a second breast region in the mammography image of the subject;
• identifying a block of pixels (Pt) with the high temperature region associated with a breast lesion within the first identified breast region;
• estimating a location (l) of the breast lesion corresponding to the identified block of pixels (Pt);
• determining, using a first machine learning model, a block of pixels (Pm) on the mammography image corresponding to the location (l) of the block of pixels (Pt) within the second breast region;
• and
• generating a report with an annotated mammography image with a marking of a determined block of pixels (Pm) on the mammography image of the subject corresponding to the block of pixels (Pt) associated with the high temperature regions on the thermal image to enable lesion identification on the mammography image of the subject.

A non-transitory computer-readable storage medium storing the one or more sequence of instructions, which when executed by one or more processors, causes to perform a method for annotating mammography images of a subject using thermal images and mammography images of the subject by determining a block of pixels on the mammography images corresponding to high temperature regions on the thermal images of the subject comprising,

• capturing a thermal image of the subject using a thermal imaging device;
• capturing the mammography image of the subject using a mammography imaging device;
• identifying a first breast region in the thermal image of the subject;
• identifying a second breast region in the mammography image of the subject;
• identifying a block of pixels (Pt) with the high temperature region associated with a breast lesion within the first identified breast region;
• estimating a location (l) of the breast lesion corresponding to the identified block of pixels (Pt);
• determining, using a first machine learning model, a block of pixels (Pm) on the mammography image corresponding to the location (l) of the block of pixels (Pt) within the second breast region;
• and
• generating a report with an annotated mammography image with a marking of a determined block of pixels (Pm) on the mammography image of the subject corresponding to the block of pixels (Pt) associated with the high temperature regions on the thermal image to enable lesion identification on the mammography image of the subject.