A dual-stage method for lesion segmentation on digital mammograms.
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Summary
This article presents a method for automatic delineation of lesion boundaries on digital mammograms using a geometric active contour model that minimizes an energy function based on the homogeneities inside and outside of the evolving contour.
- Type
- article
- Published
- 2007-11-01
- Cited by
- 112
- References
- 38
- OpenAlex
- https://openalex.org/W18072482
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:17188537
Keywords
Computer science
References
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- Level Set Methods and Fast Marching Methods: Evolving Interfaces in Computational Geometry, Fluid Mechanics, Computer Vision, and Materials Science (2nd edition)
- Cancer Statistics, 2007
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- A new 2D segmentation method based on dynamic programming applied to computer aided detection in mammography.
- Solid breast nodules: use of sonography to distinguish between benign and malignant lesions.
- A two-stage method for lesion segmentation on digital mammograms
- Segmentation of suspicious densities in digital mammograms.
- Combined adaptive enhancement and region-growing segmentation of breast masses on digitized mammograms.
- Level set methods and dynamic implicit surfaces
- Nonlinear total variation based noise removal algorithms
- Snakes: Active contour models
- Fully automatic segmentation of the brain in MRI
- MR imaging of the breast for the detection, diagnosis, and staging of breast cancer.
- Computer-aided characterization of mammographic masses: accuracy of mass segmentation and its effects on characterization
- Level set evolution without re-initialization: a new variational formulation
Cited by
- Segmentation and detection of breast cancer in mammograms combining wavelet analysis and genetic algorithm
- Towards Automatic Image Analysis for Computerised Mammography
- Automatic mass segmentation on mammograms combining random walks and active contour
- Computer Aided Detection in Mammography
- Development and Evaluation of Computerized Segmentation Algorithm for 3D Multimodality Breast Images
- Tracking fuzzy borders using geodesic curves with application to liver segmentation on planning CT.
- Lesion border detection in dermoscopy images using dynamic programming
- Grid-Enabled Quantitative Analysis of Breast Cancer
- Dependence of Shape-Based Descriptors and Mass Segmentation Areas on Initial Contour Placement Using the Chan-Vese Method on Digital Mammograms
- Deep structured learning for mass segmentation from mammograms
- A novel computer aided breast mass detection scheme based on morphological enhancement and SLIC superpixel segmentation.
- Tree RE-weighted belief propagation using deep learning potentials for mass segmentation from mammograms
- A two-stage method for microcalcification cluster segmentation in mammography by deformable models.
- A review of automatic mass detection and segmentation in mammographic images
- A Feature Selection Method Base on GA for CBIR Mammography CAD
- Marker-Controlled Watershed for Lesion Segmentation in Mammograms
- Image enhancement and edge-based mass segmentation in mammogram
- Impact of lesion segmentation metrics on computer-aided diagnosis/detection in breast computed tomography
- Hybrid segmentation of mass in mammograms using template matching and dynamic programming.
- Image Enhancement and Its Effects on Segmentation for Mammographic Masses
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