Adaptive segmentation of lesions in medical images
AssigneeInternational Business Machines Corporation
InventorAlon Hazan
Life of this patent
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Abstract
A method comprising using at least one hardware processor for: receiving a digital medical image and a binary image mask, wherein the binary image mask depicts a segmentation of a lesion in the digital medical image; computing a plurality of layers of the lesion; for each of the plurality of layers of the lesion, extracting layer features; and sending the extracted layer features to a lesion classifier.
Claims20
A method comprising using at least one hardware processor for:
- receiving a digital medical image and a binary image mask, wherein the binary image mask depicts a segmentation of a lesion in the digital medical image;
- computing a plurality of layers of the lesion;
- for each of the plurality of layers of the lesion, extracting layer features;
- and
- sending the extracted layer features to a lesion classifier.
A computer program product for lesion feature extraction, the computer program product comprising a non-transitory computer-readable storage medium having program code embodied therewith, the program code executable by at least one hardware processor to:
- receive a digital medical image and a binary image mask, wherein the binary image mask depicts a segmentation of a lesion in the digital medical image;
- compute a plurality of layers of the lesion;
- for each of the plurality of layers of the lesion, extract layer features;
- and
- send the extracted layer features to a lesion classifier.
A system for lesion feature extraction, comprising:
- at least one hardware processor;
- a non-transitory computer-readable storage medium comprising program code embodied therewith, the program code executable by the at least one hardware processor to:
- i) receive a digital medical image and a binary image mask, wherein the binary image mask depicts a segmentation of a lesion in the digital medical image;
- ii) compute a plurality of layers of the lesion;
- iii) for each of the plurality of layers of the lesion, extract layer features;
- and
- iv) send the extracted layer features to a lesion classifier.
Dependencies are inferred from the claim text.