24-09-2016, 04:42 PM
1456151090-SynopsisAIMS.docx (Size: 25.41 KB / Downloads: 4)
Objective of the project:
Detection of Breast Cancer by fusing Mammogram and Thermogram images using Image Processing Techniques.
Scope of the project:
Advances and ongoing improvements in imaging technologies have improved the sensitivity of breast cancer detection and diagnosis, but each modality is most beneficial when utilized according to individual traits such as age, risk, and breast density. Mammography is considered the “gold standard” in the evaluation of the breast lesions from an imaging perspective. Ultrasound examination and magnetic resonance imaging are being offered as diagnostic techniques and as adjuncts to the pre and postoperative workup. Despite all of these advances, it is still the case that no single imaging modality is capable of identifying and characterising all breast abnormalities and a combined modality approach will continue to be necessary. In this overview we evaluate the role of various imaging techniques in the diagnosis of breast cancer.
Abstract:
Breast cancer is a malignant tumor that starts in the cells of the breast. A malignant tumor is a group of cancer cells that can grow into nearby tissues or spread to distant parts of the body. Breast cancer is the most common disease amongest women. Mammography is the standard method of diagnosing breast cancer; but Infrared Breast thermography is a imaging technique that provides information based on the temperature changes in breast.
Thermography is a noninvasive, fast and painless imaging techinquesthat is able to detect breast tumors much earlier than the traditional mammography methods. Thermal or infrared radiations emited from human body are higher around the regions where a tumor is present due to its low cell activity. The thermal information can be shown in a pseudo coloured image where each colour represents a specific range of tempretrure. Based on segmentation region of interest of a hot region followed by colour analysis is extracted. Depending of shape, size and borders the abnormalities is determined.
Using Neural Network and Image Processing Techniques we are trying to improve the detection of Breast cancer. Since there already exists many algorithms, by combining these algorithms it helps in achieving higher sensitivy and detection. Also during clinical examination mammography and IR images were combined and a sensitivity of 98% was achieved and we are aiming to do the same.