Abstract
AbstractImage 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.
Funder
Qatar National Research Fund
Hamad Medical Corporation
Publisher
Springer Science and Business Media LLC
Subject
Urology,Computer Science (miscellaneous),Computer Networks and Communications,Computer Science Applications,Computational Mathematics,Biochemistry, Genetics and Molecular Biology (miscellaneous)
Reference52 articles.
1. Abadi M, Barham P, Chen J, Chen Z, Davis A, Dean J, Devin M, Ghemawat S, Irving G, Isard M, Kudlur M, Levenberg J, Monga R, Moore S, Murray DG, Steiner B, Tucker P, Vasudevan V, Warden P, Wicke M, Yu Y, Zheng X (2016) Tensorflow: a system for large-scale machine learning. In: Proceedings of the 12th USENIX conference on operating systems design and implementation. OSDI’16. USENIX Association, USA, pp 265–283
2. AlZubi S, Islam N, Abbod M (2011) Multiresolution analysis using wavelet, ridgelet, and curvelet transforms for medical image segmentation. J Biomed Imaging 2011:4. https://doi.org/10.1155/2011/136034
3. Ansari MY, Yang Y, Meher PK, Dakua SP (2022) Dense-psp-unet: a neural network for fast inference liver ultrasound segmentation. Comp Biol Med. https://doi.org/10.1016/j.compbiomed.2022.106478
4. Avants BB, Epstein CL, Grossman M, Gee JC (2008) Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Med Image Anal 12(1):26–41. https://doi.org/10.1016/j.media.2007.06.004
5. Balakrishnan G, Zhao A, Sabuncu MR, Guttag J, Dalca AV (2019) Voxelmorph: a learning framework for deformable medical image registration. IEEE Trans Med Imaging 38(8):1788–1800. https://doi.org/10.1109/TMI.2019.2897538
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献