医学图像分割

医学图像分割的主流方法之一是基于水平集(Level Set)的分割方法。目前针对主流的分割方法,我们主体研究思路如下图




模型凸化以及形状先验两个方面,未开展相关工作。



参考文献(部分演示代码-参数随图像需要调整):

[7] Xiaomeng Xin, Lingfeng Wang, Chunhong Pan, Shigang Liu:Adaptive regularization level set  evolution for medical image segmentation and bias field correction. International Conference on Image Processing 2015: 1006-1010

[6] Lingfeng Wang, Chunhong Pan, Explicit Order Model for Region-based Level Set Segmentation, International Conference on Acoustics,Speech, and Signal Processing, 2015

[5] Lingfeng Wang (Corresponding Author), Chunhong Pan, Robust Level Set Image Segmentation via a Local Correntropy-based K-means Clustering, PatternRecognition, 2014

PR_Code.rar

[4] Lingfeng Wang (Corresponding Author), Chunhong Pan, Image Guided Regularization Level Set Evolution for MR Image Segmentation and Bias Field Correction,Magnetic Resonance Imaging, 2013

[3] Lingfeng Wang (Corresponding Author), Huaiyu Wu,Chunhong Pan, Region-based Image Segmentation with Local Signed Difference Energy, Pattern RecognitionLetters, 2013

PRLetters_Code.zip

[2] Lingfeng Wang (Corresponding Author), Zeyun Yu, Chunhong Pan, A Unified Level Set Framework Utilizing Parameter Priors for Medical Image Segmentation, Science China (Series F), 1-14, 2012 (This is the extension version of ACCV 2010)  

ACCV_CHINA_Science_Segmentation.zip

[1] Ying Wang, Lingfeng Wang, Shiming Xiang, Chunhong Pan, Level Set Evolution with Locally  Linear Classification for Image Segmentation,International Conference on Image Processing, 2011 (The entension version is accepted by Pattern Recognition)

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