Graph Cuts and Efficient N-D Image Segmentation
International Journal of Computer Vision
Random Walks for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
IStar: A Raster Representation for Scalable Image and Volume Data
IEEE Transactions on Visualization and Computer Graphics
Graph spectral image smoothing using the heat kernel
Pattern Recognition
Kinetic Modeling Based Probabilistic Segmentation for Molecular Images
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Semi-supervised prostate cancer segmentation with multispectral MRI
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
User-friendly interactive image segmentation through unified combinatorial user inputs
IEEE Transactions on Image Processing
Fast random walker with priors using precomputation for interactive medical image segmentation
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part III
Beta-measure for probabilistic segmentation
MICAI'10 Proceedings of the 9th Mexican international conference on Advances in artificial intelligence: Part I
Detecting brain activation in fMRI using group random walker
MICCAI'10 Proceedings of the 13th international conference on Medical image computing and computer-assisted intervention: Part II
Object tracking and segmentation in a closed loop
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part I
A unified approach to segmentation and categorization of dynamic textures
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
Random walks for deformable image registration
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Probabilistic multi-shape segmentation of knee extensor and flexor muscles
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part III
A video depth refinement with circuit model constraint
SIGGRAPH Asia 2011 Posters
An energy minimization approach to the data driven editing of presegmented images/volumes
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
Pedestrian image segmentation via shape-prior constrained random walks
PSIVT'11 Proceedings of the 5th Pacific Rim conference on Advances in Image and Video Technology - Volume Part II
EGSR'08 Proceedings of the Nineteenth Eurographics conference on Rendering
A survey of graph theoretical approaches to image segmentation
Pattern Recognition
Prior knowledge, random walks and human skeletal muscle segmentation
MICCAI'12 Proceedings of the 15th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Closed-Form relaxation for MRF-MAP tissue classification using discrete laplace equations
MICCAI'12 Proceedings of the 15th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
Spectral Image Segmentation Using Image Decomposition and Inner Product-Based Metric
Journal of Mathematical Imaging and Vision
Fiber connectivity integrated brain activation detection
IPMI'13 Proceedings of the 23rd international conference on Information Processing in Medical Imaging
Integrating tracking with fine object segmentation
Image and Vision Computing
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The recently introduced random walker segmentation algorithm of [14] has been shown to have desirable theoretical properties and to perform well on a wide variety of images in practice. However, this algorithm requires user-specified labels and produces a segmentation where each segment is connected to a labeled pixel. We show that incorporation of a nonparametric probability density model allows for an extended random walkers algorithm that can locate disconnected objects and does not require user-specified labels. Finally, we show that this formulation leads to a deep connection with the popular graph cuts method of [8, 24].