Interactive Organ Segmentation Using Graph Cuts
MICCAI '00 Proceedings of the Third International Conference on Medical Image Computing and Computer-Assisted Intervention
An Intelligent System Approach to Higher-Dimensional Classification of Volume Data
IEEE Transactions on Visualization and Computer Graphics
Hybrid Segmentation and Exploration of the Human Lungs
Proceedings of the 14th IEEE Visualization 2003 (VIS'03)
Liver segmentation from computed tomography scans: A survey and a new algorithm
Artificial Intelligence in Medicine
A comparative evaluation of interactive segmentation algorithms
Pattern Recognition
Human Understandable Features for Segmentation of Solid Texture
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Interactive level set segmentation for image-guided therapy
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Oriented Boundary Graph: A Framework to Design and Implement 3D Segmentation Algorithms
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Uncertainty-Aware Guided Volume Segmentation
IEEE Transactions on Visualization and Computer Graphics
Toward a generic evaluation of image segmentation
IEEE Transactions on Image Processing
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This paper presents an interactive method for 3D images segmentation. This method is based on a region adjacency graph representation that improves and simplifies the segmentation process. This graph representation allows the user to easily define some splitting and merging operations which gives the possibility to make an incremental construction of the final segmentation. To validate the interest of the proposed method, our interactive proposition has been integrated into a volumetric texture segmentation process. The obtained results are very satisfactory even in the case of complex volumetric textures. This same system, including the textural features and our interactive proposition, has been manipulated by specialists in sonography to segment 3D ultrasound images of the skin. Some examples of segmentation are presented to illustrate the interactivity of our approach.