Multimodality multiparameter medical imaging and image analysis

Since the advent of X-rays, medical imaging and computerized image analysis have made significant contributions in diagnostic radiology and health care. Several imaging modalities have been developed to acquire anatomical and functional information about human body and organs. These modalities differ in basic principles of image acquisition but provide, in most cases, complementary information to define a physiological process. It is important to acquire and analyze all of the information describing the specific anatomical and functional behavior for diagnosis, treatment and therapeutic intervention. It becomes apparent that synergetic multidisciplinary efforts involving researchers from medicine, biological sciences, physics, chemistry, mathematics, and engineering and computer science are needed for further advancement of existing imaging technologies. Such a synergy is also needed to invent new multiparameter imaging technologies to improve understanding and modeling of physiological behavior which could be used for early diagnosis of specific diseases and to devise better methods of treatment, intervention and clinical management. Future trends may include a virtual environment of interactions among researchers and clinicians through global databases and information processing modules involving models, simulations and clinical trials. This talk will present an overview of some advanced medical imaging modalities such as multi-parameter MRI and then present model-based adaptive tissue segmentation methods from brain images for detection and characterization of brain pathologies. Recent research results for analysis of multi-parameter brain MR images involving brain tumor and stroke characterization will be presented. Also, multi-parameter multi-spectral optical imaging for characterizing skin cancer will be presented.