Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geodesic Saliency of Watershed Contours and Hierarchical Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
The watershed transform: definitions, algorithms and parallelization strategies
Fundamenta Informaticae - Special issue on mathematical morphology
Partitioning 3D Surface Meshes Using Watershed Segmentation
IEEE Transactions on Visualization and Computer Graphics
Watersnakes: Energy-Driven Watershed Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
The Image Foresting Transform: Theory, Algorithms, and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hybrid image segmentation using watersheds and fast region merging
IEEE Transactions on Image Processing
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Watershed transform has been widely used in medical image segmentation. One fundamental problem with it is over-segmentation. There are mainly two approaches to deal with this problem: hierarchical segmentation and segmentation with markers. The markers, either automatically extracted or interactively generated, are mostly used in the homotopy modification of morphological gradients prior to the watershed segmentation. Most of the current techniques does not incorporate domain knowledge of the data. In this paper, we propose a two-step marker-controlled watershed segmentation algorithm with simple domain knowledge incorporated: (1) Modified image foresting transform (IFT) algorithm is used to produce the initial segmentation; (2) The marker-controlled watershed region merging process is incorporated with domain knowledge. A min-cut criterion for region merging is proposed. This approach is effectively applied to the interactive 3D heart chamber partitioning.