Interactive segmentation of plexiform neurofibroma tissue: method and preliminary performance evaluation.
Plexiform neurofibromas (PNs) are a major manifestation of neurofibromatosis-1 (NF1), a common genetic disease involving the nervous system. Treatment decisions are mostly based on a gross assessment of changes in tumor using MRI. Accurate volumetric measurements are rarely performed in this kind of...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 50; no. 8; pp. 877 - 885 |
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| Autores principales: | , , , , , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
Aug2012
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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=104358300&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104358300 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Aug2012 vid: 50 iid: 8 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104358300 NLM22707229 2011623085 10.1007/s11517-012-0929-1 NLM22707229 104358300 ppf: 877 ppct: 8 formats: fmt: @attributes: type: P tig: atl: Interactive segmentation of plexiform neurofibroma tissue: method and preliminary performance evaluation. aug: au: Weizman L Hoch L Ben Bashat D Joskowicz L Pratt LT Constantini S Ben Sira L Weizman, Lior Hoch, Lior Ben Bashat, Dafna Joskowicz, Leo Pratt, Li-tal Constantini, Shlomi Ben Sira, Liat affil: School of Engineering and Computer Science, The Hebrew University of Jerusalem, Jerusalem, Israel sug: subj: Image Interpretation, Computer Assisted Methods Magnetic Resonance Imaging Methods Neurofibroma Pathology Information Science Methods User-Computer Interface Algorithms Artificial Intelligence Human Observer Bias Pilot Studies Reproducibility of Results Sensitivity and Specificity ab: Plexiform neurofibromas (PNs) are a major manifestation of neurofibromatosis-1 (NF1), a common genetic disease involving the nervous system. Treatment decisions are mostly based on a gross assessment of changes in tumor using MRI. Accurate volumetric measurements are rarely performed in this kind of tumors mainly due to its great dispersion, size, and multiple locations. This paper presents a semi-automatic method for segmentation of PN from STIR MRI scans. The method starts with a user-based delineation of the tumor area in a single slice and automatically segments the PN lesions in the entire image based on the tumor connectivity. Experimental results on seven datasets, with lesion volumes in the range of 75-690 ml, yielded a mean absolute volume error of 10 % (after manual adjustment) as compared to manual segmentation by an expert radiologist. The mean computation and interaction time was 13 versus 63 min for manual annotation. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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