A central factor in the success and increasingly wide-spread application of imaging-based approaches in medicine has been the emergence of sophisticated mathematical and computational methods for extracting, analyzing and integrating clinically significant and scientifically important information from image data. The Penn Image Computing and Science Laboratory is at the forefront of research and education in all of the quantitative methods represented, including: segmentation, registration, morphometry and shape analysis, with numerous interdisciplinary collaborations spanning a variety of organ systems and all of the major and emerging modalities in biological/biomaterials imaging and in vivo medical imaging.
The major area of the laboratory’s research and development is in the field of Biomedical Image Analysis, with particular focus on computational methods for quantifying the ways in which anatomy can vary in nature, over time, or as a consequence of disease or intervention. These methods aim to improve the detection of subtle changes on imaging studies and thus the specificity and reliability of diagnosis in patients with diseases who exhibit such changes and for whom there are often no known clinical diagnostic procedures. A precise understanding of normal and pathological variations in anatomy is also prerequisite for accurate localization of function that is critical to the success of imaging studies of organ structure-function relationships in health and disease. Internationally recognized for seminal contributions to computational anatomy, PICSL’s current work spans numerous collaborations across a variety of disciplines and includes applications of image analysis to study the biomechanics of moving organs; the normal development and pathological correlates of brain structure; and the correlation between brain structural changes and cognitive deficits in central nervous system disorders.
A primary goal of this research is to translate into practical tools and make freely and publicly available cutting-edge image analysis methods that are essential for extracting the most information from medical imaging data. PICSL’s founding role in the development of the open-source Insight Toolkit combined with the toolkit’s use for all software development, maintenance and dissemination at the laboratory ensures long-term continuity of support of the developed tools. In addition, PICSL is the inaugural collaboration partner of the National Centers for Biomedical Computing, which are specifically charged to foster translational research in biomedical computing.
This research is also complementary to the laboratory’s educational activities, which focus on training that is at the interface between medicine and the engineering and computational sciences. PICSL has been a principal architect of a newly awarded initiative from the Howard Hughes Medical Institute (HHMI) and NIH to develop an interdisciplinary Ph.D. program in Clinical Imaging and Informational Sciences. This HHMI-NIBIB Interface Award will establish and develop the infrastructure for a new graduate program in biomedical image science.
PICSL is a part of the graduate groups of the Departments of Computer and Information Science, and Bioengineering. It is affiliated with the Centers for Functional Neuroimaging, forBioinformatics and for Cognitive Neuroscience, the Institutes for Medicine and Engineering and for Translational Medicine and Therapeutics, the General Robotics, Automation, Sensing and Perception Laboratory, the Working Group on Applied Mathematics and Computational Science, and the Leonard Davis Institute of Health Economics, and is a founding member of the Center for Health Informatics at Penn, the Penn Center for Musculoskeletal Disorders, and the National Library of Medicine Insight Consortium.