Method and electric device for processing breast Tomosynthesis images

An electrical device, comprising:

• a memory storing a plurality of instructions;
• and
• a processor communicatively connected to the memory and is configured to execute the instructions,
• wherein the processor is configured to obtain a plurality of breast images at a plurality of levels and perform a binarization operation and a pooling operation to at least one marked breast image of the breast images to generate at least one lesion mask, wherein the at least one lesion mask comprises a plurality of values to represent if there is a lesion or not,
• wherein the processor is configured to train a convolutional neural network according to the breast images and the at least one lesion mask, wherein the convolutional neural network comprises a first branch and a second branch, the first branch is configured to output at least one value to indicate whether a lesion exists, the second branch is configured to output a heat map, and loss values between the heat map and the at least one lesion mask are configured to train the convolutional neural network,
• wherein the processor is configured to obtain a plurality of cropped images from the breast images at different levels according to a particular two-dimensional position, and input each of the cropped images into the convolutional neural network to obtain a plurality of cropped heat maps,
• wherein the processor is configured to input the cropped heat maps into a recurrent neural network in an order of the levels to obtain a plurality of output heat maps, combine the output heat maps to obtain a first integrated heat map, and train the recurrent neural network according to loss values between the first integrated heat map and the at least one lesion mask.