Automatic segmentation of cortical vessels in pre- and post-tumor resection laser range scan images

Siyi Ding; Michael I. Miga; Reid C. Thompson; Ishita Garg; Benoit M. Dawant

doi:10.1117/12.811702

10 March 2009 Automatic segmentation of cortical vessels in pre- and post-tumor resection laser range scan images

Siyi Ding, Michael I. Miga, Reid C. Thompson, Ishita Garg, Benoit M. Dawant

Proceedings Volume 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling; 726104 (2009) https://doi.org/10.1117/12.811702
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

Measurement of intra-operative cortical brain movement is necessary to drive mechanical models developed to predict sub-cortical shift. At our institution, this is done with a tracked laser range scanner. This device acquires both 3D range data and 2D photographic images. 3D cortical brain movement can be estimated if 2D photographic images acquired over time can be registered. Previously, we have developed a method, which permits this registration using vessels visible in the images. But, vessel segmentation required the localization of starting and ending points for each vessel segment. Here, we propose a method, which automates the segmentation process further. This method involves several steps: (1) correction of lighting artifacts, (2) vessel enhancement, and (3) vessels' centerline extraction. Result obtained on 5 images obtained in the operating room suggests that our method is robust and is able to segment vessels reliably.

Citation Download Citation

Siyi Ding, Michael I. Miga, Reid C. Thompson, Ishita Garg, and Benoit M. Dawant "Automatic segmentation of cortical vessels in pre- and post-tumor resection laser range scan images", Proc. SPIE 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling, 726104 (10 March 2009); https://doi.org/10.1117/12.811702

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