3 July 2001 Semiautomatic bone removal technique from CT angiography data
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Cortical bone is the major barrier in visualizing the 3-D blood vessel tree from CT Angiography [CTA] data. Thus, we have developed a novel semi-automatic technique that removes the cortical bone and retains the clinical diagnostic information such as blood vessels, aneurysms, and calcifications. The technique is based on a methodical composite set of filters that use region-growing, adaptive, and morphological filtering algorithms. While using only voxel intensity value and region size information, this technique retains most of the CTA data untouched. We have implemented this method on 10 CTA abdomen and head data sets. The accuracy of the method was tested and proved successful by visual inspection of all segmented slices. The segmented CTA data were also visualized in 3-D with different Ray Casting Volume Rendering techniques (e.g. Maximum Intensity Projection). The blood vessels along with other diagnostic information were clearly visualized in 3-D without the obstruction of bone. The segmentation technique ran under one second per slice (image size is 512x512x2 bytes) on a PC with 550 MHz processor.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Abdal Majeid Alyassin, Abdal Majeid Alyassin, Gopal B. Avinash, Gopal B. Avinash, } "Semiautomatic bone removal technique from CT angiography data", Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); doi: 10.1117/12.431005; https://doi.org/10.1117/12.431005

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