查到的一些论文，这方面工作很多，后面会继续更新。

文章都没看，看完会写进一步的笔记。

Sci-Hub地址：http://sci-hub.tw/

Brain aneurysm segmentation in CTA and 3DRA using Geodesic Active Regions based on second order prototype features and non parametric density estimation
来源：Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); doi: 10.1117/12.596237;
问题：CTA和3DRA的动脉瘤分割
方法：用密度估计和GAR(geodesic active regions)

Development of Image Segmentation Methods for Intracranial Aneurysms
来源：Computational and Mathematical Methods in Medicine Volume 2013, Article ID 715325
问题：CTA的动脉瘤分割
方法：使用已有的Region Growing Threshold和Chan-Vese model方法，提出新的Threshold-Based Level Set方法

Segmentation and Separation of Cerebral Aneurysms : A Multi-Phase Approach
来源：8th International Symposium on Image and Signal Processing and Analysis (ISPA 2013)
问题：CTA的动脉瘤分割
方法：先分割血管，手动指定动脉瘤内部的seed，形态学方法分割动脉瘤，水平集方法refine

Intracranial aneurysm segmentation in 3D CT angiography: Method and quantitative validation with and without prior noise filtering
来源：European Journal of Radiology Volume 79, Issue 2, August 2011, Pages 299-304
问题：CTA动脉瘤分割
方法：GAC(Geodesic Active Contours)

Intracranial Aneurysm Segmentation in 3D CT Angiography: Method and Quantitative Validation
来源：Proceedings of SPIE - The International Society for Optical Engineering 7623 · March 2010
问题：CTA的动脉瘤分割
方法：GAC(Geodesic Active Contours)

Automatedand segmentation of cerebral vasculature with aneurysms in 3DRA and TOF-MRA using geodesic active regions: An evaluation study
来源：Med Phys. 2011 Jan;38(1):210-22.
问题：3DRA和TOF-MRA的动脉瘤分割
方法：改进的GAR(geodesic active regions)

A PCA-based approach for brain aneurysm segmentation
来源：Multidimensional Systems and Signal Processing, January 2018, Volume 29, Issue 1, pp 257–277
问题：MRA和CTA的动脉瘤分割
方法：计算梯度场，然后PCA

Study of the lattice Boltzmann method application to cerebral aneurysm segmentation
来源：博士论文，Medical Imaging. INSA de Lyon, 2014. English.
问题：CTA的动脉瘤分割(ch5)
方法：栅格Boltzman机分割大的动脉瘤，水平集refine

Segmentation of Intracranial Vessels and Aneurysms in Phase Contrast Magnetic Resonance Angiography Using Multirange Filters and Local Variances
来源：IEEE Trans Image Process. 2013 Mar;22(3):845-59. doi: 10.1109/TIP.2012.2216274. Epub 2012 Aug 30.
问题：PC-MRA的动脉瘤分割
方法：use multirange filters and local variances to extract intensity-based image features

Vessel and Intracranial Aneurysm Segmentation Using Multi-range Filters and Local Variances
来源：MICCAI 2007: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007 pp 866-874（上面一篇的会议版）
问题：PC-MRA的动脉瘤分割
方法：use multirange filters and local variances to extract intensity-based image features

Semi-automatic detection and segmentation algorithm of saccular aneurysms in 2D cerebral DSA images
来源：The Egyptian Journal of Radiology and Nuclear Medicine (2016) 47, 859–865
问题：2D投影DSA的动脉瘤分割
方法：使用Frangi filter和形态学方法划分区域，对区域分类

Feasibility of Quantification of Intracranial Aneurysm Pulsation with 4D CTA with Manual and Computer-Aided Post-Processing
来源：PLoS One. 2016 Nov 23;11(11):e0166810. doi: 10.1371/journal.pone.0166810. eCollection 2016.
问题：讨论手动和计算机辅助后处理4DCTA动脉瘤的可行性

Applying machine learning and image feature extraction techniques to the problem of cerebral aneurysm rupture
来源：这只是一个研究计划，正在实施中
问题：用机器学习方法预测动脉瘤破裂

A Review on Segmentation and Modeling of Cerebral Vasculature for Surgical Planning
来源：IEEE Access, vol. 5, pp. 15222–15240,2017
问题：脑血管分割的review

DeepVesselNet: Vessel Segmentation, Centerline Prediction, and Bifurcation Detection in 3-D Angiographic Volumes
来源：arXiv:1803.09340, 2018
问题：MRA血管分割和分支点检测
方法：CNN

Cerebral Artery Segmentation with Level Set Methods
来源：Proceedings of Image and Vision Computing New Zealand 2007, pp. 300–304,
问题：CTA脑血管分割
方法：水平集方法

Brain blood vessel segmentation using line-shaped profiles
来源：Physics in Medicine and Biology 58(22):8041-8061 · October 2013 
问题：CTA血管和血管畸形分割
方法：直线轮廓

Vessel Tortuosity and Brain Tumor Malignancy: A Blinded Study
来源：Academic Radiology Volume 12, Issue 10, October 2005, Pages 1232-1240
问题：MRA分割肿瘤处的血管
方法：手动给seed，自动得到血管skeleton，然后确定半径，用血管形状的统计特征判断是否是肿瘤

Semi-Supervised Cerebrovascular Segmentation by Hierarchical Convolutional Neural Network
来源：Access IEEE, vol. 6, pp. 67841-67852, 2018
问题：MRA的脑血管分割
方法：CNN

Atlas-based method for segmentation of cerebral vascular trees from phase-contrast magnetic resonance angiography
来源： SPIE. Medical Imaging, 2004, San Diego, United States. 5370, pp.420-431, 2004
问题：PC-MRA脑血管分割
方法：区域生长、阈值、Atlas