Breast cancer detection
View Patent ↗A hybrid detection model may be used for breast cancer detection. A system can identify a region of interest on a received mammogram. The region of interest may have a particular level of grey at each pixel of the image. A morphological and entropy filter may then each be applied to the region of interest. Based on the filters, the system may generate a hybrid result that is the average of a combination of the two filters. The system may then segment the region of interest using a selected clustering algorithm.
1. A computer-implemented method for a hybrid detection model for use in breast cancer detection, the method comprising:
identifying, responsive to receipt of a digital image, a region of interest on the digital image, wherein the region of interest is described using a level of grey for each pixel in the region of interest;
applying, to each level of grey for each pixel in the region of interest in the digital image, a predetermined morphological filter to produce a first output, wherein the morphological filter reduces grey levels of the digital image to generate a first set of values;
applying, to each level of grey for each pixel in the region of interest in the digital image, a predetermined entropy filter to produce a second output that captures a set of maximum grey values, wherein the maximum grey values reflect a local maximum relative to other grey values in the digital image;
generating a hybrid result that is a combination of the first output of the predetermined morphological filter and the second output of the predetermined entropy filter; and
segmenting, using the hybrid result, the digital image into potential microcalcifications by using a selected clustering algorithm with sub-segmentation.
2. The method of claim 1 , wherein the selected clustering algorithm includes one of a k-means and c-means.
3. The method of claim 1 , further comprising displaying, on a user interface, the segmented digital image.
4. The method of claim 1 , further comprising capturing, by a mammogram capture device, the digital image.
5. The method of claim 4 , wherein the capturing, identifying, and applying of each of the predetermined morphology filter and the predetermined entropy filter, are performed by a same device, and wherein the device includes the mammogram capture device.
6. The method of claim 5 , wherein the device is a smart phone.
7. The method of claim 1 , further comprising accessing prior to the identifying, the digital image from a database.
8. The method of claim 1 , wherein the digital image is a mammogram.
9. The method of claim 1 , wherein generating the hybrid result comprises averaging values of the first output and the second output for each pixel.
10. The method of claim 1 , wherein the predetermined morphological filter and the predetermined entropy filter are applied in parallel.
11. A computer system comprising:
A computer readable storage medium with program instructions stored thereon; and
one or more processors configured to execute the program instructions to perform a method comprising:
identifying, responsive to receipt of a digital image, a region of interest on the digital image, wherein the region of interest is described using a level of grey for each pixel in the region of interest;
applying, to each level of grey for each pixel in the region of interest in the digital image, a predetermined morphological filter to produce a first output, wherein the morphological filter reduces grey levels of the digital image to generate a first set of values;
applying, to each level of grey for each pixel in the region of interest in the digital image, a predetermined entropy filter to produce a second output that captures a set of maximum grey values, wherein the maximum grey values reflect a local maximum relative to other grey values in the digital image;
generating a hybrid result that is a combination of the first output of the predetermined morphological filter and the second output of the predetermined entropy filter; and
segmenting, using the hybrid result, the digital image into potential microcalcifications by using a selected clustering algorithm with sub-segmentation.
12. The system of claim 11 , wherein the selected clustering algorithm includes one of a k-means and c-means.
13. The system of claim 11 , wherein the method further comprises displaying, on a user interface, the segmented digital image.
14. The system of claim 11 , wherein the method further comprises capturing, by a mammogram capture device, the digital image.
15. The system of claim 11 , wherein the system further comprises a mammogram capture device.
16. The system of claim 11 , wherein the method further comprises accessing, prior to the identifying, the digital image from a database.
17. The system of claim 11 , wherein the digital image is a mammogram.
18. A computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions executable by a computer processor to cause the processor to perform a method comprising:
identifying, responsive to receipt of a digital image, a region of interest on the digital image, wherein the region of interest is described using a level of grey for each pixel in the region of interest;
applying, to each level of grey for each pixel in the region of interest in the digital image, a predetermined morphological filter to produce a first output, wherein the morphological filter reduces grey levels of the digital image to generate a first set of values;
applying, to each level of grey for each pixel in the region of interest in the digital image, a predetermined entropy filter to produce a second output that captures a set of maximum grey values, wherein the maximum grey values reflect a local maximum relative to other grey values in the digital image;
generating a hybrid result that is a combination of the first output of the predetermined morphological filter and the second output of the predetermined entropy filter; and
segmenting, using the hybrid result, the digital image into potential microcalcifications by using a selected clustering algorithm with sub-segmentation.
19. The computer program product of claim 18 , wherein the selected clustering algorithm includes one of a k-means and c-means.
20. The computer program product of claim 18 , wherein the method further comprises accessing, prior to the identifying, the digital image from a database.
21. The computer program product of claim 18 , wherein the digital image is a mammogram.