Classifying hormone receptor status of malignant tumorous tissue from breast thermographic images

A system for classifying the hormone receptor status of malignant tumorous tissue identified in a thermographic image of a breast, the system comprising:

• a storage device containing a classifier system trained to classify a hot spot as one of:
• hormone receptor positive (HR+), and hormone receptive negative (HR−);
• and
• a processor in communication with the storage device, the processor retrieving executing machine readable program instructions which, when executed by the processor, enable the processor to:
• receive thermographic image(s) of both breasts of a patient with a malignant tumorous region;
• analyze the image(s) to define a boundary contour of the breast in the image(s);
• segment the breast regions into regions of elevated temperature and otherwise;
• and
• analyze temperature distribution of the thermographic image of the whole breast and the elevated temperature regions to classify the malignant tumorous tissue as being hormone receptor positive, and hormone receptive negative otherwise, wherein said analyzing the elevated temperature regions comprises comparison of the temperature distribution of the segmented regions, wherein said analyzing for the entire breast region comprises extracting a gray-level co-occurrence matrix (GLCM) and other textural features and using the co-occurrence features of the two breasts for classifying malignant tumorous tissue,
• where a first segmented region is the elevated temperature region corresponding to the malignant tumorous tissue region;
• a second segmented region is the non-elevated temperature region in the same breast, wherein a distance measure representing a similarity between the first segmented region and the second segmented region is determined, and wherein the distance measure is provided to a classifier system to classify the hormone receptor class as either positive or negative.

A method for classifying the hormone receptor status of malignant tumorous tissue identified in a thermographic image of a breast, the method comprising:

• receiving thermographic image(s) of both breasts of a patient with a malignant tumorous region;
• analyzing the image(s) to define a boundary contour of the breast in the image(s);
• generating a temperature map by subtracting the pixel temperatures of the malignant breast with the mean temperature of the contra-lateral breast;
• computing a Run-Length-Matrix from the above temperature map, after quantizing the temperatures into L bins;
• computing textural non-uniformity features from the Run Length Matrix;
• and
• classifying the malignant tumorous tissue as hormone receptor negative if the non-uniformity feature is higher or hormone receptor positive otherwise, using a classifier system.

A method for classifying the hormone receptor status of malignant tumorous tissue identified in a thermographic image of a breast, the method comprising:

• receiving thermographic image(s) of both breasts of a patient with a malignant tumorous region;
• analyzing the image(s) to define a boundary contour of the breast in the image(s);
• segmenting the breast regions into regions of elevated temperature and otherwise;
• determining the ratio between the area of elevated temperature region(s) in the malignant tumorous breast and the area of the elevated temperature region(s) in the contralateral breast, or vice-versa by analyzing the elevated temperature regions, wherein said analysis of the elevated temperature regions comprises the step of (i) comparison of temperature distribution of the segmented regions and (ii) extracting a gray-level co-occurrence matrix (GLCM) and other textural features and using the co-occurrence features of the two breasts for classifying malignant tumorous tissue;
• providing the above area ratio and co-occurrence of features to the classifier system:
• and
• classifying the malignant tumorous region as hormone receptor positive if the ratio is higher or hormone receptor negative if the ratio is zero, using a classifier system.