Systems and methods for detecting an indication of a visual finding type in an anatomical image

A system for detection of an indication of a single visual finding type in a target anatomical image of a target individual by a single-label neural network, the single visual finding type denoting an acute medical condition for early and rapid treatment thereof, comprising:

• at least one hardware processor executing a code for:
• feeding a target anatomical image into a single-label neural network;
• and
• computing likelihood of an indication of the single visual finding type in the target anatomical image by the single-label neural network,
• wherein the single visual finding type detected by the trained single-label neural network is selected from a plurality of visual finding types detected by a trained multi-label neural network,
• wherein the single-label neural network is computed by at least one of fine-tuning and retraining the trained multi-label neural networking according to a single-label training dataset of a plurality of anatomical images labeled with an indication of the visual finding type selected from the plurality of visual finding types used for labelling of a multi-label training dataset, wherein the multi-label neural network is trained to compute likelihood of each of a plurality of visual finding types based on the multi-label training dataset of a plurality of anatomical images labeled with the plurality of visual finding types.

A method of computing a single-label neural network for detection of an indication of a single visual finding type in an anatomical image of a target individual, the single visual finding type denoting an acute medical condition for early and rapid treatment thereof, comprising:

• providing a multi-label training dataset including a plurality of anatomical images each associated with a label indicative of at least one visual finding type selected from a plurality of visual finding types, or indicative of no visual finding types;
• training a multi-label neural network for detection of the plurality of visual finding types in a target anatomical image according to the multi-label training dataset;
• creating a single-label training dataset including a plurality of anatomical images each associated with a label indicative of the single visual finding type selected from the plurality of visual finding types used for labelling of the multi-label training dataset, or indicative of an absence of the single visual finding type;
• and
• training a single-label neural network for detection of the single visual finding type in a target anatomical image, by setting the trained multi-label neural network as an initial baseline of the single-label neural network, and at least one of fine-tuning and re-training the baseline according to the single-label training dataset,
• wherein the single visual finding type detected by the trained single-label neural network is selected from the plurality of visual finding types detected by the trained multi-label neural network.