Development of Novel Computer-aided Diagnosis Systems

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A phenomenal growth in the use of digital images has been observed in recent times in medical diagnosis by physicians. Picture archiving and communications system (PACS) are being widely used in health care as it offers several advantages such as low cost, improved quality, and flexibility in sharing patient data among the health care professionals. It also opens up the possibility of using computers to speed up diagnosis and reduce subjectiveness. The computer-aided diagnosis (CAD) system are already being used for breast cancer screening in many countries, and is expected to be extended for diagnosis of many other kinds of diseases. The image analysis techniques play a key role in developing a CAD system. However, the characteristics of images vary significantly across different modalities (e.g., X-ray, CT, MRI, histopathology), tissue/organ types, and diseases. It is a huge challenge to develop image analysis techniques for such a wide variety of images. **In this proposal, we propose to carry on research in two areas: Computer aided diagnosis of Skin Cancer and Tuberculosis (TB). The skin cancer, especially Melanoma, and drug-resistant TB ared deadly diseases with high mortality rate. Early screening of these diseases through computer-aided diagnosis would be very useful in health care. In skin cancer, the proposed research will explore development of histopathological image analysis techniques to improve the diagnosis of Melanoma and Basal cell (the most frequent type of skin cancer) cancer. Techniques would be developed for analyzing both epidermis and dermis areas in a histopathological image. Techniques will also be developed for detecting clusters of nuclei, which are observed in the junction of epidermis and dermis area. Due to the noisy nature of the images, the performance of existing mitosis detection technique is low, and we would explore developing a robust mitosis detection technique based on the sparse representation and classification technique. Appropriate techniques for 3D whole slide histopathological image reconstruction and visualization will be developed to enable the pathologist to see a slide in 3D. In TB diagnosis, robust techniques would be developed for more accurate diagnosis. In addition to cavity, and acinar shadows, the "volume loss" is a hallmark of TB as a result of its destructive and fibrotic nature. The Hilar and mediastinal lymphadenopathy are good indicators of HIV-related TB, and primary TB. Techniques will be developed to detect these indicators, and reduce the false positive rate of typical primary and postprimary TB. Experiments will be conducted with larger databases and with a wider variety of images such as images with acinar shadows, atypical or normal radiographs without acinar shadows, and radiographs with nodules but without acinar shadows.**The proposed research will establish a detailed understanding of several important issues related to computer-aided diagnosis of skin cancer, and TB. To our knowledge, we are the first group working on developing a computer-aided diagnosis system for melanoma. We are also one of very few groups who are working on development of efficient computer-aided diagnosis system for TB. A successful development is expected to reduce the diagnosis time and error, and will result in intellectual property.