Classifying medical images using deep convolution neural network (CNN) architecture

A system for classifying medical images, the system comprising a processor, memory accessible by the processor, and computer program instructions stored in the memory and executable by the processor to perform:

• receiving a plurality of image tiles from a whole medical image, the whole medical image having a global image-level tag and without local annotations that reveal a position and a shape of findings within the image, each image tile including a portion of the whole image, processed by a trained or a pre-trained model and outputting a one-dimensional feature vector for each tile to generate a three-dimensional feature volume;
• and
• classifying the whole image by a trained model based on the generated three-dimensional feature volume to form a classification of the image, the trained model comprising a plurality of layers to decrease spatial dimensions of the generated three-dimensional feature volume to a singular output.

A computer program product for classifying medical images, the computer program product comprising a non-transitory computer readable storage having program instructions embodied therewith, the program instructions executable by a computer, to cause the computer to perform a method comprising:

• receiving a plurality of image tiles from a whole medical image, the whole medical image having a global image-level tag and without local annotations that reveal a position and a shape of findings within the image, each image tile including a portion of the whole image, processed by a trained or a pre-trained model and outputting a one-dimensional feature vector for each tile to generate a three-dimensional feature volume;
• and
• classifying the whole image by a trained model based on the generated three-dimensional feature volume to form a classification of the image, the trained model comprising a plurality of layers to decrease spatial dimensions of the generated three-dimensional feature volume to a singular output.