Symbiosis Centre for Medical Image Analysis (SCMIA)

In recent years there has been an increased thrust to understand and quantify the complex information conveyed by medical images. Developing modern computational techniques that offer the potential for extracting diverse and complex information from imaging data and applying these to a plethora of clinical studies is crucial. These techniques not only support precise quantification but also overcome the limitations of subjective visual interpretation. Furthermore, these methods can facilitate finding specific markers that relate to pathologies as well as aid in treatment planning. Building on this background, the objectives of this center are as follows: (1) Development of novel computer-based image analysis methods and their application to a wide variety of clinical research studies (2) Translating the techniques to the clinic thereby aiding early diagnosis and understanding of the underlying pathology (3) Develop computational imaging tools in the management of various stages of a disease or disorder including diagnosis, surgery, pre-surgery planning, and monitoring. Currently, the center focuses on neuroimaging (MRI), neuro-musculoskeletal disorders (CT and MRI), joint diseases (X-Ray, CT, and MRI), and breast imaging (Ultrasound). Image analysis methodologies include volumetric analysis, diffusion MRI processing and analysis, structural and functional connectomics, statistical learning in imaging, radiomics, population based analysis, dynamic MRI for joint motion, and deep neural networks for image segmentation, classification, and registration. The center plans to diversify research to image analysis and synthesis of various organs and include multiple modalities in imaging along with the genomics component.