Development of a cerebral aneurysm segmentation method to prevent sentinel hemorrhage
<p dir="ltr">Image segmentation being the first step is always crucial for brain aneurysm treatment planning; it is also crucial during the procedure. A robust brain aneurysm segmentation has the potential to prevent the blood leakage, also known as sentinel hemorrhage. Here, we pres...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | , |
| Published: |
2023
|
| Subjects: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | <p dir="ltr">Image segmentation being the first step is always crucial for brain aneurysm treatment planning; it is also crucial during the procedure. A robust brain aneurysm segmentation has the potential to prevent the blood leakage, also known as sentinel hemorrhage. Here, we present a method combining a multiresolution and a statistical approach in two dimensional domain to segment cerebral aneurysm in which the Contourlet transform (CT) extracts the image features, while the Hidden Markov Random Field with Expectation Maximization (HMRF-EM) segments the image, based on the spatial contextual constraints. The proposed algorithm is tested on Three-Dimensional Rotational Angiography (3DRA) datasets; the average values of segmentation accuracy, DSC, FPR, FNR, specificity, and sensitivity, are found to be 99.72%, 93.52%, 0.07%, 5.23%, 94.77%, and 99.96%, respectively.</p><h2>Other Information</h2><p dir="ltr">Published in: Network Modeling Analysis in Health Informatics and Bioinformatics<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1007/s13721-023-00412-7" target="_blank">https://dx.doi.org/10.1007/s13721-023-00412-7</a></p> |
|---|