Patch-Based Segmentation with Spatial Consistency: Application to MS Lesions in Brain MRI.
This paper presents an automatic lesion segmentation method based on similarities between multichannel patches. A patch database is built using training images for which the label maps are known. For each patch in the testing image, k similar patches are retrieved from the database. The matching lab...
| Publicado en: | International Journal of Biomedical Imaging pp. 1 - 14 |
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| Autores principales: | , , |
| Formato: | diagnostic images equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
1/24/2016
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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=113599839&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 113599839 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 16874188 1WZI jtl: International Journal of Biomedical Imaging issn: 16874188 maglogo: N pubinfo: dt: 1/24/2016 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 113599839 113599839 113599839 10.1155/2016/7952541 113599839 ppf: 1 ppct: 13 formats: tig: atl: Patch-Based Segmentation with Spatial Consistency: Application to MS Lesions in Brain MRI. aug: au: Mechrez, Roey Goldberger, Jacob Greenspan, Hayit affil: Biomedical Engineering Department, Tel-Aviv University, 69978 Tel Aviv, Israel sug: subj: Magnetic Resonance Imaging Multiple Sclerosis Skin Tests Diagnostic Imaging Brain Descriptive Statistics Probability Scales Sensitivity and Specificity ab: This paper presents an automatic lesion segmentation method based on similarities between multichannel patches. A patch database is built using training images for which the label maps are known. For each patch in the testing image, k similar patches are retrieved from the database. The matching labels for these k patches are then combined to produce an initial segmentation map for the test case. Finally an iterative patch-based label refinement process based on the initial segmentation map is performed to ensure the spatial consistency of the detected lesions. The method was evaluated in experiments on multiple sclerosis (MS) lesion segmentation in magnetic resonance images (MRI) of the brain. An evaluation was done for each image in the MICCAI 2008 MS lesion segmentation challenge. Results are shown to compete with the state of the art in the challenge. We conclude that the proposed algorithm for segmentation of lesions provides a promising new approach for local segmentation and global detection in medical images. pubtype: Academic Journal doctype: diagnostic images equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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