Methods for polyp detection

A method for polyp detection comprising:

• applying a convolutional neural network (CNN) to an image of the colon, wherein applying the CNN comprises:
• selecting a first set of sub-regions of the image by applying a first convolution stage of the CNN to the image, the first convolution stage comprising a first polyp-positive filter that identifies sub-regions of the image containing a polyp-like feature;
• selecting a second set of sub-regions from the first set of sub-regions by applying a second convolution stage of the CNN to the first set of sub-regions, the second convolution stage comprising a second polyp-positive filter that identifies the incidence of a polyp-like feature in a sub-region and a polyp-negative filter that identifies the incidence of a non-polyp feature in a sub-region;
• selecting a third set of sub-regions by identifying sub-regions in the second set of sub-regions where a ratio of the incidence of the polyp-like feature to the incidence of the non-polyp feature exceeds a pre-determined threshold;
• and
• generating an output that indicates the presence of a polyp within the image if the number of sub-regions in the third set of sub-regions meets or exceeds a pre-determined count threshold.

A method for polyp detection, the method comprising:

• acquiring an image from an imaging module located at a distal portion of an endoscope;
• identifying surface peaks in the image;
• identifying clusters of surface peaks based on a predetermined threshold separation distance;
• selecting a surface peak from each identified cluster;
• defining a pixel region around each of the selected surface peaks;
• comparing an image feature in each of said defined pixel regions with a corresponding image feature of a plurality of images containing polyps and a corresponding image feature of a plurality of images that do not contain polyps;
• the comparing of the pixel region with a corresponding image containing polyps further comprising applying a first convolution stage of the CNN to the pixel region, the first convolution stage comprising a polyp-positive filter that identifies sub-regions of the image containing a polyp-like feature;
• the comparing of the pixel region with a corresponding image containing polyps further comprising applying a second convolution stage of the CNN to the pixel region, the second convolution stage comprising a polyp-negative filter that identifies the incidence of a non-polyp feature in a sub-region;
• and
• if the image feature in a defined pixel region matches the corresponding image feature of a plurality of images containing polyps, generating a notification that a polyp has been detected.