Semi-automated intracranial aneurysm segmentation and neck detection

Nam H. Le; Edgar A. Samaniego; Ashrita Raghuram; Sebastian Sanchez; Honghai Zhang; Milan Sonka

doi:10.1117/12.2613145

4 April 2022 Semi-automated intracranial aneurysm segmentation and neck detection

Nam H. Le, Edgar A. Samaniego, Ashrita Raghuram, Sebastian Sanchez, Honghai Zhang, Milan Sonka

Proceedings Volume 12032, Medical Imaging 2022: Image Processing; 1203238 (2022) https://doi.org/10.1117/12.2613145
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Conference Poster

Abstract

dentification of the neck of unruptured intracranial aneurysms is essential for quantitative analysis and monitoring of disease progression. Given a limited number of available tools for neck detection and measurements, physicians have little choices when it comes to producing clinically accurate metrics. This research presents a novel method of aneurysm neck detection based on semi-automated segmentation of aneurysm and its associated vessels. The reported aneurysm segmentation method utilizes LOGISMOS-JEI1 as its foundation to form a novel global-optimality-guaranteeing strategy for quantitative analysis of aneurysm morphology.

Citation Download Citation

Nam H. Le, Edgar A. Samaniego, Ashrita Raghuram, Sebastian Sanchez, Honghai Zhang, and Milan Sonka "Semi-automated intracranial aneurysm segmentation and neck detection", Proc. SPIE 12032, Medical Imaging 2022: Image Processing, 1203238 (4 April 2022); https://doi.org/10.1117/12.2613145

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