MRI brain image segmentation for spotting tumors using improved mountain clustering approach

Nishchal K. Verma, Payal Gupta, Pooja Agrawal, Yan Cui

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

This paper presents improved mountain clustering technique based MRI (magnetic resonance imaging) brain image segmentation for spotting tumors. The proposed technique is compared with some existing techniques such as K-Means and FCM, clustering. The performance of all these clustering techniques is compared in terms of cluster entropy as a measure of information and also is visually compared for image segmentation of various brain tumor MRI images . The cluster entropy is heuristically determined, but is found to be effective in forming correct clusters as verified by visual assessment.

Original languageEnglish (US)
Title of host publicationApplied Imagery Pattern Recognition 2009
Subtitle of host publicationVision: Humans, Animals, and Machines, AIPR 2009
DOIs
StatePublished - Dec 1 2009
Event38th Applied Imagery Pattern Recognition Workshop: Vision: Humans, Animals, and Machines, AIPRW 2009 - Washington, DC, United States
Duration: Oct 14 2009Oct 16 2009

Publication series

NameProceedings - Applied Imagery Pattern Recognition Workshop
ISSN (Print)1550-5219

Other

Other38th Applied Imagery Pattern Recognition Workshop: Vision: Humans, Animals, and Machines, AIPRW 2009
CountryUnited States
CityWashington, DC
Period10/14/0910/16/09

Fingerprint

Magnetic resonance
Image segmentation
Tumors
Brain
Entropy
Imaging techniques

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

Verma, N. K., Gupta, P., Agrawal, P., & Cui, Y. (2009). MRI brain image segmentation for spotting tumors using improved mountain clustering approach. In Applied Imagery Pattern Recognition 2009: Vision: Humans, Animals, and Machines, AIPR 2009 [5466301] (Proceedings - Applied Imagery Pattern Recognition Workshop). https://doi.org/10.1109/AIPR.2009.5466301

MRI brain image segmentation for spotting tumors using improved mountain clustering approach. / Verma, Nishchal K.; Gupta, Payal; Agrawal, Pooja; Cui, Yan.

Applied Imagery Pattern Recognition 2009: Vision: Humans, Animals, and Machines, AIPR 2009. 2009. 5466301 (Proceedings - Applied Imagery Pattern Recognition Workshop).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Verma, NK, Gupta, P, Agrawal, P & Cui, Y 2009, MRI brain image segmentation for spotting tumors using improved mountain clustering approach. in Applied Imagery Pattern Recognition 2009: Vision: Humans, Animals, and Machines, AIPR 2009., 5466301, Proceedings - Applied Imagery Pattern Recognition Workshop, 38th Applied Imagery Pattern Recognition Workshop: Vision: Humans, Animals, and Machines, AIPRW 2009, Washington, DC, United States, 10/14/09. https://doi.org/10.1109/AIPR.2009.5466301
Verma NK, Gupta P, Agrawal P, Cui Y. MRI brain image segmentation for spotting tumors using improved mountain clustering approach. In Applied Imagery Pattern Recognition 2009: Vision: Humans, Animals, and Machines, AIPR 2009. 2009. 5466301. (Proceedings - Applied Imagery Pattern Recognition Workshop). https://doi.org/10.1109/AIPR.2009.5466301
Verma, Nishchal K. ; Gupta, Payal ; Agrawal, Pooja ; Cui, Yan. / MRI brain image segmentation for spotting tumors using improved mountain clustering approach. Applied Imagery Pattern Recognition 2009: Vision: Humans, Animals, and Machines, AIPR 2009. 2009. (Proceedings - Applied Imagery Pattern Recognition Workshop).
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