System and method for detection and classification of findings in images

A method for detection and classification of findings in an image, comprising:

• receiving the image;
• processing said image by a first plurality of convolutional and pooling layers of a neural network to produce a plurality of feature maps, each one of said plurality of feature maps comprising a plurality of location coordinates related to said image;
• processing one of said plurality of feature maps by some of said first plurality of convolutional and pooling layers, a second plurality of convolutional and pooling layers and a first plurality of fully connected layers of said neural network to produce a plurality of region proposals;
• producing a plurality of region of interest (ROI) pools by using a third plurality of pooling layers of said neural network to downsample said plurality of region proposals with each one of said plurality of feature maps;
• processing said plurality of ROI pools by at least one pool concatenation layer of said neural network to produce a combined ROI pool;
• processing said combined ROI pool by a classification network comprising some other of said first plurality of convolutional and pooling layers to produce one or more classifications;
• and
• outputting said one or more classifications.

A system for detection and classification of findings in an image, comprising:

• at least one hardware processor configured to:
• receive the image;
• receive a plurality of values of a plurality of attributes related to said image;
• process said plurality of values by a first plurality of fully connected layers of a neural network to produce a plurality of processed values;
• integrate said plurality of processed values into a plurality of layers of said neural network;
• process said image by a first plurality of convolutional and pooling layers of a neural network to produce at least one feature map, each one of said at least one feature map comprising a plurality of location coordinates related to said image;
• process one of said at least one feature map by some of said first plurality of convolutional and pooling layers, a second plurality of convolutional and pooling layers and a second plurality of fully connected layers of said neural network to produce a plurality of region proposals;
• produce a plurality of region of interest (ROI) pools by using a third plurality of pooling layers of said neural network to downsample said plurality of region proposals with each one of said at least one feature map;
• process said plurality of ROI pools by at least one pool concatenation layer to produce a combined ROI pool;
• process said combined ROI pool by a classification network comprising some other of said first plurality of convolutional and pooling layers to produce one or more classifications;
• and
• output said one or more classifications.