Bioimage Suite: A structural, functional and metabolic image analysis platform

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While both medical imaging acquisition and medical image analysis technology have made enormous progress over the last 20 years, the full power of three-dimensional imaging is still not being fully utilized for evaluating both clinical and basic science hypotheses. This is, in part, due to the lack of easy to use, easily available software that includes state-of-the-art analysis methods. Biolmage Suite represents a coalescence of software development efforts originating at Yale in Image Processing and Analysis, Magnetic Resonance and PET (positron emission tomography) research centers that already incorporates functionality for many image analysis tasks including both automated and interactive segmentation of structural and angiography images, estimation of rigid/non-rigid registration and non-rigid deformation (e.g. in cardiac images) between images, and analysis of functional (fMRI) and diffusion tensor (DTI) magnetic resonance images and will include functionality to process magnetic resonance spectroscopy (MRS), Single Photon Emission Computed Tomography (SPECT), and PET images. Many of the included methods originated as a result of original research in the Yale imaging groups. The fundamental objective of this grant application is to extend, document and further test this software in order to provide a practical software suite for imaging researchers and enable us to freely disseminate it to researchers both at Yale and at other research institutions. We propose.the following specific aims. (1) Expand the underlying algorithm base of Biolmage Suite by the addition of a carefully selected set of additional methods. (2) Improve the graphical user interface currently available in Biolmage Suite and add extensive support for database integration that will simplify the task of processing the large sets of images needed for testing hypotheses, (3) Test and verify the correctoperation of the software and (4) Fully document the software and make it freely available to the research community. Relevance to Public Health: The availability of advanced computer programs for processing medical images will substantially improve the utilization of medical imaging technology which is a key tool in understanding many important diseases (e.g. diabetes, cardiovascular disease, autism, epilepsy), planning therapy (e.g. neurosurgery) and evaluating other proposed treatment procedures (e.g. new drugs)