Isoperimetric graph partitioning for image segmentation

IEEE Transactions on Pattern Analysis and Machine Intelligence
Leo Grady, Eric L Schwartz

Abstract

Spectral graph partitioning provides a powerful approach to image segmentation. We introduce an alternate idea that finds partitions with a small isoperimetric constant, requiring solution to a linear system rather than an eigenvector problem. This approach produces the high quality segmentations of spectral methods, but with improved speed and stability.

References

Apr 30, 2004·Nature Immunology·Christine Grady

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Citations

Mar 1, 2012·PloS One·Jan EggerChristopher Nimsky
Oct 23, 2012·Medical Image Analysis·Marc Niethammer, Christopher Zach
Nov 26, 2015·Medical Image Analysis·Xiaofan ZhangShaoting Zhang
May 29, 2012·Scientific Reports·Jan EggerTina Kapur
May 9, 2014·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society· Jingdong Wang Long Quan
Feb 26, 2014·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Jianbing ShenXuelong Li
Mar 20, 2010·IEEE Transactions on Pattern Analysis and Machine Intelligence·Dorit S Hochbaum
Aug 21, 2010·IEEE Transactions on Pattern Analysis and Machine Intelligence·Wei FengZhi-Qiang Liu
Oct 27, 2006·IEEE Transactions on Pattern Analysis and Machine Intelligence·Leo Grady
Aug 2, 2008·IEEE Transactions on Medical Imaging·Hsun-Hsien ChangChien Ho
Feb 24, 2011·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Thomas SchoenemannDaniel Cremers
Dec 15, 2015·IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society·Xingping DongLuc Van Gool
Sep 29, 2015·IEEE Transactions on Medical Imaging·Fuyong XingLin Yang
Sep 8, 2009·NeuroImage·Suresh A SadananthanVitali Zagorodnov
Oct 16, 2015·International Journal for Numerical Methods in Biomedical Engineering·A DanilovYu Vassilevski
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Aug 16, 2017·IEEE Transactions on Neural Networks and Learning Systems·Chunjie ZhangQi Tian
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Sep 5, 2019·Contrast Media & Molecular Imaging·Feng-Ping An, Zhi-Wen Liu

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