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3D Visualization of Brain Tumor and Tissue from Medical Volumetric Images

並列摘要


This paper proposes an approach integrating level set method with ray casting for image segmentation and visualization. A prior probability derived from "Kullback-Leibler" information number to estimate the targets (e.g., tumor and tissue) is firstly incorporated into Bayesian level set method. The Bayesian level set method is then used to continuously segment the targets from a series of brain images. To facilitate 3D volume visualization of medical-image dataset, ray casting and marching cubes algorithm are conducted to render the targets and construct the surface of the targets. Experiment results are finally reported in terms of segmenting, rendering, and surface reconstructing of the tumor, tissue, and whole brain.

被引用紀錄


Sun, C. Y. (2009). 基於貝氏曲線的果蠅腦模型三維特徵平均與變形研究 [master's thesis, National Tsing Hua University]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0016-1111200916121137
Lin, C. L. (2009). 以多段三次貝式曲管為基礎的表面模型特徵半自動擷取技術 [master's thesis, National Tsing Hua University]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0016-1111200916121136

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