Isfahan University of Medical Sciences

Science Communicator Platform

Stay connected! Follow us on X network (Twitter):
Share By
Automatic Brain Aneurysm Extraction in Angiography Videos Using Circlet Transform and a Modified Level Set Model Publisher

Summary: Research developed a method to spot brain aneurysms in X-ray videos, improving surgery safety. #BrainHealth #MedicalImaging

Momeni S1 ; Sarrafzadeh O1, 2 ; Rabbani H1, 3
Authors

Source: Current Medical Imaging Reviews Published:2018


Abstract

Background: These days, many attempts have been done to specify the size and location of aneurysms, leading to more successful surgical operation and less bleeding risk. In this paper, a novel method is proposed to extract brain aneurysms from two dimensional x-ray angiography videos, automatically. Methods: The most acute challenges in detecting brain aneurysm are the complexity of vessel structures and shape similarity between the aneurysm and vessel overlaps and vessel cross sections. Therefore, researchers regarded removing vessel structures as an initial and crucial step to detect aneurysm. Since the circularity feature is the most distinctive criteria for physicians to detect aneurysm, firstly, we proposed a robust method based on Fast Circlet Transform (FCT) to localize the aneurysm without needing to remove vessel structures. Then, to segment the detected aneurysm more accurately, a modified Level Set algorithm is proposed. Finally, our proposed method is quantitatively evaluated on two different datasets with different views, shapes, sizes, locations and contrast. Results & Conclusion: Experimental results show that the proposed system is reliable without dealing with vessel structure removal challenges, reluctant false positive candidates, hard parameter tuning and poor edge gradient. © 2018 Bentham Science Publishers.
1. Circlet Based Framework for Optic Disk Detection, Proceedings - International Conference on Image Processing, ICIP (2017)
2. Vesselness-Guided Active Contour: A Coronary Vessel Extraction Method, Journal of Medical Signals and Sensors (2014)
Experts (# of related papers)
Automatic Brain Aneurysm Extraction in Angiography Videos Using Circlet Transform and a Modified Level Set Model
Other Related Docs
6. Covid Tv-Unet: Segmenting Covid-19 Chest Ct Images Using Connectivity Imposed Unet, Computer Methods and Programs in Biomedicine Update (2021)
7. Diabetic Retinopathy Grading by Digital Curvelet Transform, Computational and Mathematical Methods in Medicine (2012)
8. Non-Rigid Registration of Fluorescein Angiography and Optical Coherence Tomography Via Scanning Laser Ophthalmoscope Imaging, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (2017)
11. Offline Handwritten Signature Verification Based on Circlet Transform and Statistical Features, Iranian Conference on Machine Vision and Image Processing, MVIP (2020)
12. Automatic Detection of Micro-Aneurysms in Retinal Images Based on Curvelet Transform and Morphological Operations, Proceedings of SPIE - The International Society for Optical Engineering (2013)
15. Circlet Transform in Cell and Tissue Microscopy, Optics and Laser Technology (2020)
16. The Ellipselet Transform, Journal of Medical Signals and Sensors (2019)
17. A Review of Coronary Vessel Segmentation Algorithms, Journal of Medical Signals and Sensors (2011)
18. Vessel Centerlines Extraction From Fundus Fluorescein Angiogram Based on Hessian Analysis of Directional Curvelet Subbands, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings (2013)
19. Extraction of Retinal Blood Vessels by Curvelet Transform, Proceedings - International Conference on Image Processing, ICIP (2009)