Systems and methods for generating summary medical images

A computer implemented method for generating summary images from sequentially acquired real time 2D medical images, comprising:

• in a plurality of iterations:
• receiving a 2D medical image captured in real time;
• computing an amount of similarity between the 2D medical image and at least one previously obtained sequence of 2D medical images;
• in response to the amount of similarity being below a threshold, determining that the 2D medical image represents an end of a slab of a plurality of sequentially obtained 2D medical images;
• aggregating the plurality of sequentially obtained 2D images of the slab into a summary image;
• and
• presenting the summary image on a display.

A computer implemented method for generating summary images from 3D medical images, comprising:

• receiving a 3D medical image;
• dividing the 3D medical images into a sequence of a plurality 2D images;
• computing a similarity dataset indicative of an amount of similarity between each pair of the plurality of 2D images;
• segmenting the similarity dataset into a plurality of slabs by minimizing the amount of similarity between consecutive slabs and maximizing the amount of similarity within each slab;
• aggregating, for each respective slab, the plurality of 2D images into a respective summary image;
• inputting each respective summary image into a summary machine learning model trained on a training dataset of a plurality of sample summary images and corresponding at least one finding depicted therein indicative of ground truth;
• and
• obtaining a score indicative of at least one finding depicted in the summary image as an outcome of the summary machine learning model.