Fusing Markov Random Fields with Anatomical Knowledge and Shape Based Analysis to Segment Multiple Sclerosis White Matter Lesions in Magnetic Resonance Images of the Brain

Stephan Al-Zubi; Klaus D. Toennies; Nils Bodammer; Hermann Hinrichs

doi:10.1007/978-3-642-55983-9_42

ScienceGate Book Chapters

BOOK-CHAPTER

Fusing Markov Random Fields with Anatomical Knowledge and Shape Based Analysis to Segment Multiple Sclerosis White Matter Lesions in Magnetic Resonance Images of the Brain

Stephan Al-Zubi Klaus D. Toennies Nils Bodammer Hermann Hinrichs

Year: 2002 Informatik aktuell Pages: 185-188 Publisher: Springer Nature

DOI: 10.1007/978-3-642-55983-9_42

Get Full-Text PDF Get Analytical Report

Keywords:

Voxel Artificial intelligence Pattern recognition (psychology) Markov random field Computer science Multiple sclerosis Feature (linguistics) White matter Computer vision Segmentation Magnetic resonance imaging Image segmentation Medicine Radiology

Metrics

Cited By

0.27

FWCI (Field Weighted Citation Impact)

Refs

0.58

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Medical Image Segmentation Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Digital Imaging for Blood Diseases

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

AI in cancer detection

Physical Sciences → Computer Science → Artificial Intelligence

Fusing Markov Random Fields with Anatomical Knowledge and Shape Based Analysis to Segment Multiple Sclerosis White Matter Lesions in Magnetic Resonance Images of the Brain

Metrics

Citation History

Topics

Related Documents

Fusing Markov random fields with anatomical knowledge and shape-based analysis to segment multiple sclerosis white matter lesions in magnetic resonance images of the brain

Vein segmentation using shape-based Markov Random Fields

Probabilistic Multiple Sclerosis Lesion Detection using Superpixels and Markov Random Fields

Most edges in Markov random fields for white matter hyperintensity segmentation are worthless

Robust Face Recognition with Occlusion by Fusing Image Gradient Orientations with Markov Random Fields