Humans are limited in their ability to detect and diagnose disease. In addition, the vast amount of image data that is generated by some imaging devices makes the detection of potential disease a burdensome task and may cause oversight errors. Another problem is that the similar characteristics of some abnormal and normal lesions may cause interpretational errors. In order to understand the disease process at its early stage, it is becoming more important to perform quantitative analysis in addition to qualitative evaluation.

Towards this perspective, automating the analysis of multidimensional medical information (images and signals) is extremely promising to improve diagnostic and therapeutic quality of tomorrow's medical practice. Modern medical imaging technology offers a broad range of new ways to examine a patient in order to diagnose and to prescribe a proper treatment. In clinical practice today, the physicians access to the imaging devices they need and to the large amount of digital data they produce. The challenge of diagnosis and proper pre-therapeutic planning is to identify relevant information from the large collection of often disparate images.

The remarkable developments in medical imaging intensified by useful image processing, pattern analysis and machine intelligence techniques, have led to the development of computer aided diagnostic systems.

[b]The School of Medical Science & Technology, IIT Kharagpur[/b] is actively involved in multidisciplinary teaching and research in medical imaging and instrumentation, image processing and pattern analysis, epidemiological analysis medical statistics, biomaterials and tissue engineering, reproductive biology and medical biotechnology, cancer biology and wound healing.

To keep pace with the latest global trends, the school organizes the short term course on [b]'Image Processing and Pattern Recognition for Early Diagnosis of Disease'[/b] for interested group of faculties, scientists, engineers, biologists, medical professionals and researchers from various academic and R&D sectors. This scientific event will allow the participants to avail an opportunity to get exposed to recent developments in diverse areas of Image and signal Processing, Disease Pattern Recognition and Statistical techniques in Medical Imaging for early diagnosis of diseases.