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25 March 2016 Improved superficial brain hemorrhage visualization in susceptibility weighted images by constrained minimum intensity projection
Marcelo A. Castro, Dzung L. Pham, John Butman
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Proceedings Volume 9789, Medical Imaging 2016: PACS and Imaging Informatics: Next Generation and Innovations; 97890D (2016) https://doi.org/10.1117/12.2216959
Event: SPIE Medical Imaging, 2016, San Diego, California, United States
Abstract
Minimum intensity projection is a technique commonly used to display magnetic resonance susceptibility weighted images, allowing the observer to better visualize hemorrhages and vasculature. The technique displays the minimum intensity in a given projection within a thick slab, allowing different connectivity patterns to be easily revealed. Unfortunately, the low signal intensity of the skull within the thick slab can mask superficial tissues near the skull base and other regions. Because superficial microhemorrhages are a common feature of traumatic brain injury, this effect limits the ability to proper diagnose and follow up patients. In order to overcome this limitation, we developed a method to allow minimum intensity projection to properly display superficial tissues adjacent to the skull. Our approach is based on two brain masks, the largest of which includes extracerebral voxels. The analysis of the rind within both masks containing the actual brain boundary allows reclassification of those voxels initially missed in the smaller mask. Morphological operations are applied to guarantee accuracy and topological correctness, and the mean intensity within the mask is assigned to all outer voxels. This prevents bone from dominating superficial regions in the projection, enabling superior visualization of cortical hemorrhages and vessels.
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Marcelo A. Castro, Dzung L. Pham, and John Butman "Improved superficial brain hemorrhage visualization in susceptibility weighted images by constrained minimum intensity projection", Proc. SPIE 9789, Medical Imaging 2016: PACS and Imaging Informatics: Next Generation and Innovations, 97890D (25 March 2016); https://doi.org/10.1117/12.2216959
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