Systems and methods for analyzing mr images depicting residual breast tissue

A computer implemented method for segmentation of FGT in a MR image, comprising:

• feeding an MR image depicting a whole breast of a target subject that excludes an implant and on which no surgical removal has been performed into a FGT segmentation ML model;
• and
• obtaining a segmentation of FGT of the MR image as an outcome of the FGT segmentation ML model,
• wherein the FGT segmentation ML model is trained on a FGT segmentation training dataset of a plurality of FGT segmentation records, each FGT segmentation record including an MR image of a segmented whole breast of a control subject that excludes an implant and on which no surgical removal has been performed, and a ground truth comprising a segmentation of the FGT depicted in the segmented whole breast,
• wherein the segmentation of the FGT is performed by:
• co-registration between a first type of MR image of the whole breast of the control subject, and a second type of MR image of the whole breast of the control subject, the first type of MR image does not suppresses signals from fat tissue and the second type of MR image does suppress signals from fat tissue;
• applying a first threshold to the first MR image such that voxels with gray scale values below the first threshold to generate a first mask;
• applying a second threshold to the second MR image such that voxels with gray scale values above the second threshold to generate a second mask;
• and
• labelling voxels that appear in the first mask and in the second mask as FGT.

A computer implemented method for training a FGT segmentation ML model for segmentation of FGT in a MR image, comprising:

• creating a FGT segmentation training dataset of a plurality of FGT segmentation records, each FGT segmentation record including an MR image of a segmented whole breast of a control subject that excludes an implant and on which no surgical removal has been performed, and a ground truth comprising a segmentation of the FGT depicted in the segmented whole breast,
• wherein the segmentation of the FGT is performed by:
• co-registration between a first type of MR image of the whole breast of the control subject, and a second type of MR image of the whole breast of the control subject, the first type of MR image does not suppresses signals from fat tissue and the second type of MR image does suppress signals from fat tissue,
• applying a first threshold to the first MR image such that voxels with gray scale values below the first threshold to generate a first mask,
• applying a second threshold to the second MR image such that voxels with gray scale values above the second threshold to generate a second mask, and
• labelling voxels that appear in the first mask and in the second mask as FGT;
• and
• training the FGT segmentation ML model on the FGT segmentation training dataset.