Detection of pulmonary nodules in CT images based on fuzzy integrated active contour model and hybrid parametric mixture model

DOI10.1155/2013/515386zbMath1275.92050OpenAlexW2077750147WikidataQ36838645 ScholiaQ36838645MaRDI QIDQ382611

Shanxing Ou, Lianfang Tian, Kan Chen, Yao Yeboah, Bin Li

Publication date: 21 November 2013

Published in: Computational \& Mathematical Methods in Medicine (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2013/515386

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Biomedical imaging and signal processing (92C55) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

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Classification of pulmonary nodules by using hybrid features

Cites Work

• Geodesic active contours
• Active contours without edges
• Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation
• Minimization of Region-Scalable Fitting Energy for Image Segmentation
• Localizing Region-Based Active Contours
• Fuzzy Energy-Based Active Contours
• Iterative Narrowband-Based Graph Cuts Optimization for Geodesic Active Contours With Region Forces (GACWRF)