Abstract: The present application provides a compound comprising at least one isotopically labeled nitrogen atom for use in diagnosing a condition or disease in a subject, compositions and kits comprising the compound and methods of using the same.

Abstract: The present application provides a compound comprising at least one isotopically labeled nitrogen atom for use in diagnosing a condition or disease in a subject, compositions and kits comprising the compound and methods of using the same.

Abstract: The present application provides a compound comprising at least one isotopically labeled nitrogen atom for use in diagnosing a condition or disease in a subject, compositions and kits comprising the compound and methods of using the same.

Abstract: A novel multiscale approach that combines segmentation with classification to detect abnormal brain structures in medical imagery, and demonstrate its utility in detecting multiple sclerosis lesions in 3D MRI data. The method uses segmentation to obtain a hierarchical decomposition of a multi-channel, anisotropic MRI scan. It then produces a rich set of features describing the segments in terms of intensity, shape, location, and neighborhood relations. These features are then fed into a decision tree-based classifier, trained with data labeled by experts, enabling the detection of lesions in all scales. Unlike common approaches that use voxel-by-voxel analysis, our system can utilize regional properties that are often important for characterizing abnormal brain structures. Experiments show successful detections of lesions in both simulated and real MR images.