Nasopharyngeal carcinoma segmentation via HMRF-EM with maximum entropy
- 1 August 2015
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE) in 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
- Vol. 2015 (1094687X), 2968-2972
- https://doi.org/10.1109/embc.2015.7319015
Abstract
This paper presents a novel automatic nasopharyngeal carcinoma segmentation approach used in magnetic resonance images. Adaptive calculation of the nasopharyngeal region location is first performed. The contour of the tumor is determined through distance regularized level set evolution with the initial contour obtained by the nearest neighbor graph model. To further refine the segmentation, a hidden Markov random field model with maximum entropy (HMRF-EM) is introduced to model the spatial information with prior knowledge. The proposed method is tested on magnetic resonance images of 26 nasopharyngeal carcinoma patients, and achieves good results.Keywords
This publication has 12 references indexed in Scilit:
- Detection of Pulmonary Nodules in CT Images Based on Fuzzy Integrated Active Contour Model and Hybrid Parametric Mixture ModelComputational and Mathematical Methods in Medicine, 2013
- Nasopharyngeal carcinoma segmentation using a region growing techniqueInternational Journal of Computer Assisted Radiology and Surgery, 2011
- Semi-automatic level set segmentation of liver tumors combining a spiral-scanning technique with supervised fuzzy pixel classificationMedical Image Analysis, 2010
- Level-set segmentation of brain tumors using a threshold-based speed functionImage and Vision Computing, 2010
- Adaptive Thresholding based on SOM Technique for Semi-Automatic NPC Image SegmentationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2009
- Nasopharyngeal Carcinoma Lesion Segmentation from MR Images by Support Vector MachinePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2006
- Efficient Graph-Based Image SegmentationInternational Journal of Computer Vision, 2004
- Level-set evolution with region competition: automatic 3-D segmentation of brain tumorsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Segmentation and visualization of nasopharyngeal carcinoma using MRIComputers in Biology and Medicine, 2003
- Markov Random Field Modeling in Computer VisionPublished by Springer Science and Business Media LLC ,1995