A Cooperative Approach Based on Local Detection of Similarities and Discontinuities for Brain MR Images Segmentation.
This paper introduces a new cooperative multi-agent approach for segmenting brain Magnetic Resonance Images (MRIs). MRIs are manually processed by human radiology experts for the identification of many diseases and the monitoring of their evolution. However, such a task is time-consuming and depends...
| Publicado en: | Journal of Medical Systems Vol. 44; no. 9 |
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| Autores principales: | , , , , |
| Formato: | diagnostic images equations & formulas tables/charts Journal Article |
| Publicado: |
Springer Nature
Sep2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=145404939&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 145404939 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Sep2020 vid: 44 iid: 9 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 145404939 145404939 145404939 10.1007/s10916-020-01610-w 145404939 ppct: 1 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: A Cooperative Approach Based on Local Detection of Similarities and Discontinuities for Brain MR Images Segmentation. aug: au: Bennai, Mohamed T. Mazouzi, Smaine Guessoum, Zahia Mezghiche, Mohamed Cormier, Stéphane affil: LIMOSE Laboratory, Faculty of Sciences, University of M'hamed Bougara of Boumerdes, Avenue de l'indépendance, 35000, Boumerdes, Algeria sug: subj: Brain Radiography Magnetic Resonance Imaging Diagnostic Imaging Image Enhancement Image Processing, Computer Assisted Brain Pathology ab: This paper introduces a new cooperative multi-agent approach for segmenting brain Magnetic Resonance Images (MRIs). MRIs are manually processed by human radiology experts for the identification of many diseases and the monitoring of their evolution. However, such a task is time-consuming and depends on expert decision, which can be affected by many factors. Therefore, various types of research were and are still conducted to automate MRI processing, mainly MRI segmentation. The approach presented in this paper, without any parametrization or prior knowledge, uses a set of situated agents, locally interacting to segment images according to two main phases: the detection of discontinuities and the detection of similarities. An implementation of this approach was tested on phantom brain MR images to assess the results and prove its efficiency. Experimental results ensure a minimum of 89% Dice coefficient with increasing values of the noise and the intensity non-uniformity. pubtype: Academic Journal doctype: diagnostic images equations & formulas tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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