NEPHROBLASTOMA ANALYSIS IN MRI IMAGES

The annotation of the tumour from medical scans is a crucial step in nephroblastoma treatment. Therefore, an accurate and reliable segmentation method is needed to facilitate the evaluation and the treatments of the tumour. The proposed method serves this purpose by performing the segmentation of ne...

Full description

Saved in:
Bibliographic Details
Published in:Image analysis & stereology 2019-01, Vol.38 (2), p.173-183
Main Authors: Kaba, Djibril, McFarlane, Nigel, Dong, Feng, Graf, Norbert, Ye, Xujiong
Format: Article
Language:English
Subjects:
Continuous Max-Flow
Graph Segmentation
Kernel Induced Space
MRI images
Nephroblastoma
Wilms tumour
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 183
container_issue 2
container_start_page 173
container_title Image analysis & stereology
container_volume 38
creator Kaba, Djibril
McFarlane, Nigel
Dong, Feng
Graf, Norbert
Ye, Xujiong
description The annotation of the tumour from medical scans is a crucial step in nephroblastoma treatment. Therefore, an accurate and reliable segmentation method is needed to facilitate the evaluation and the treatments of the tumour. The proposed method serves this purpose by performing the segmentation of nephroblastoma in MRI scans. The segmentation is performed by adapting and a 2D free hand drawing tool to select a region of interest in the scan slices. Results from 24 patients show a mean root-mean-square error of 0.0481 ± 0.0309, an average Dice coefficient of 0.9060 ± 0.0549 and an average accuracy of 99.59% ± 0.0039. Thus the proposed method demonstrated an effective agreement with manual annotations.
doi_str_mv 10.5566/ias.2000
format article
fullrecord <record><control><sourceid>doaj_cross</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_fc89a8d2903d417c865a8ee8807400db</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_fc89a8d2903d417c865a8ee8807400db</doaj_id><sourcerecordid>oai_doaj_org_article_fc89a8d2903d417c865a8ee8807400db</sourcerecordid><originalsourceid>FETCH-LOGICAL-c288t-96c02bbdf223b9b13804f2c45a591d656c9792ddf88e642798922b8ca97932203</originalsourceid><addsrcrecordid>eNo9kM1Kw0AURgdRsFbBR8hGcJN6585P7ixjqW0gaaWpC1fDZCaRlEok6ca3N7Xi6vs4i7M4jN1zmCml9VPrhhkCwAWbcFIyVlyry_ErglhwYa7ZzTDsAaRGpSbsYb14XW03z3la7jZFGqXrNH8vszLK1lGxzaKsSJeL8pZdNe4w1Hd_O2VvL4vdfBXnm2U2T_PYI9ExNtoDVlVoEEVlKi4IZINeKqcMD1ppbxKDITREtZaYGDKIFXk3YoEIYsqyszd0bm-_-vbT9d-2c639BV3_YV1_bP2hto0n4yigAREkTzxp5aiuiSCRAKEaXY9nl--7Yejr5t_HwZ5S2TGVPaUSP7wdVag</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>NEPHROBLASTOMA ANALYSIS IN MRI IMAGES</title><source>Free Full-Text Journals in Chemistry</source><creator>Kaba, Djibril ; McFarlane, Nigel ; Dong, Feng ; Graf, Norbert ; Ye, Xujiong</creator><creatorcontrib>Kaba, Djibril ; McFarlane, Nigel ; Dong, Feng ; Graf, Norbert ; Ye, Xujiong</creatorcontrib><description>The annotation of the tumour from medical scans is a crucial step in nephroblastoma treatment. Therefore, an accurate and reliable segmentation method is needed to facilitate the evaluation and the treatments of the tumour. The proposed method serves this purpose by performing the segmentation of nephroblastoma in MRI scans. The segmentation is performed by adapting and a 2D free hand drawing tool to select a region of interest in the scan slices. Results from 24 patients show a mean root-mean-square error of 0.0481 ± 0.0309, an average Dice coefficient of 0.9060 ± 0.0549 and an average accuracy of 99.59% ± 0.0039. Thus the proposed method demonstrated an effective agreement with manual annotations.</description><identifier>ISSN: 1580-3139</identifier><identifier>EISSN: 1854-5165</identifier><identifier>DOI: 10.5566/ias.2000</identifier><language>eng</language><publisher>Slovenian Society for Stereology and Quantitative Image Analysis</publisher><subject>Continuous Max-Flow ; Graph Segmentation ; Kernel Induced Space ; MRI images ; Nephroblastoma ; Wilms tumour</subject><ispartof>Image analysis &amp; stereology, 2019-01, Vol.38 (2), p.173-183</ispartof><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,778,782,27907,27908</link.rule.ids></links><search><creatorcontrib>Kaba, Djibril</creatorcontrib><creatorcontrib>McFarlane, Nigel</creatorcontrib><creatorcontrib>Dong, Feng</creatorcontrib><creatorcontrib>Graf, Norbert</creatorcontrib><creatorcontrib>Ye, Xujiong</creatorcontrib><title>NEPHROBLASTOMA ANALYSIS IN MRI IMAGES</title><title>Image analysis &amp; stereology</title><description>The annotation of the tumour from medical scans is a crucial step in nephroblastoma treatment. Therefore, an accurate and reliable segmentation method is needed to facilitate the evaluation and the treatments of the tumour. The proposed method serves this purpose by performing the segmentation of nephroblastoma in MRI scans. The segmentation is performed by adapting and a 2D free hand drawing tool to select a region of interest in the scan slices. Results from 24 patients show a mean root-mean-square error of 0.0481 ± 0.0309, an average Dice coefficient of 0.9060 ± 0.0549 and an average accuracy of 99.59% ± 0.0039. Thus the proposed method demonstrated an effective agreement with manual annotations.</description><subject>Continuous Max-Flow</subject><subject>Graph Segmentation</subject><subject>Kernel Induced Space</subject><subject>MRI images</subject><subject>Nephroblastoma</subject><subject>Wilms tumour</subject><issn>1580-3139</issn><issn>1854-5165</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNo9kM1Kw0AURgdRsFbBR8hGcJN6585P7ixjqW0gaaWpC1fDZCaRlEok6ca3N7Xi6vs4i7M4jN1zmCml9VPrhhkCwAWbcFIyVlyry_ErglhwYa7ZzTDsAaRGpSbsYb14XW03z3la7jZFGqXrNH8vszLK1lGxzaKsSJeL8pZdNe4w1Hd_O2VvL4vdfBXnm2U2T_PYI9ExNtoDVlVoEEVlKi4IZINeKqcMD1ppbxKDITREtZaYGDKIFXk3YoEIYsqyszd0bm-_-vbT9d-2c639BV3_YV1_bP2hto0n4yigAREkTzxp5aiuiSCRAKEaXY9nl--7Yejr5t_HwZ5S2TGVPaUSP7wdVag</recordid><startdate>20190101</startdate><enddate>20190101</enddate><creator>Kaba, Djibril</creator><creator>McFarlane, Nigel</creator><creator>Dong, Feng</creator><creator>Graf, Norbert</creator><creator>Ye, Xujiong</creator><general>Slovenian Society for Stereology and Quantitative Image Analysis</general><scope>AAYXX</scope><scope>CITATION</scope><scope>DOA</scope></search><sort><creationdate>20190101</creationdate><title>NEPHROBLASTOMA ANALYSIS IN MRI IMAGES</title><author>Kaba, Djibril ; McFarlane, Nigel ; Dong, Feng ; Graf, Norbert ; Ye, Xujiong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c288t-96c02bbdf223b9b13804f2c45a591d656c9792ddf88e642798922b8ca97932203</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Continuous Max-Flow</topic><topic>Graph Segmentation</topic><topic>Kernel Induced Space</topic><topic>MRI images</topic><topic>Nephroblastoma</topic><topic>Wilms tumour</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kaba, Djibril</creatorcontrib><creatorcontrib>McFarlane, Nigel</creatorcontrib><creatorcontrib>Dong, Feng</creatorcontrib><creatorcontrib>Graf, Norbert</creatorcontrib><creatorcontrib>Ye, Xujiong</creatorcontrib><collection>CrossRef</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Image analysis &amp; stereology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kaba, Djibril</au><au>McFarlane, Nigel</au><au>Dong, Feng</au><au>Graf, Norbert</au><au>Ye, Xujiong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>NEPHROBLASTOMA ANALYSIS IN MRI IMAGES</atitle><jtitle>Image analysis &amp; stereology</jtitle><date>2019-01-01</date><risdate>2019</risdate><volume>38</volume><issue>2</issue><spage>173</spage><epage>183</epage><pages>173-183</pages><issn>1580-3139</issn><eissn>1854-5165</eissn><abstract>The annotation of the tumour from medical scans is a crucial step in nephroblastoma treatment. Therefore, an accurate and reliable segmentation method is needed to facilitate the evaluation and the treatments of the tumour. The proposed method serves this purpose by performing the segmentation of nephroblastoma in MRI scans. The segmentation is performed by adapting and a 2D free hand drawing tool to select a region of interest in the scan slices. Results from 24 patients show a mean root-mean-square error of 0.0481 ± 0.0309, an average Dice coefficient of 0.9060 ± 0.0549 and an average accuracy of 99.59% ± 0.0039. Thus the proposed method demonstrated an effective agreement with manual annotations.</abstract><pub>Slovenian Society for Stereology and Quantitative Image Analysis</pub><doi>10.5566/ias.2000</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 1580-3139
ispartof Image analysis & stereology, 2019-01, Vol.38 (2), p.173-183
issn 1580-3139
1854-5165
language eng
recordid cdi_doaj_primary_oai_doaj_org_article_fc89a8d2903d417c865a8ee8807400db
source Free Full-Text Journals in Chemistry
subjects Continuous Max-Flow
Graph Segmentation
Kernel Induced Space
MRI images
Nephroblastoma
Wilms tumour
title NEPHROBLASTOMA ANALYSIS IN MRI IMAGES
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-16T10%3A32%3A30IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-doaj_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=NEPHROBLASTOMA%20ANALYSIS%20IN%20MRI%20IMAGES&rft.jtitle=Image%20analysis%20&%20stereology&rft.au=Kaba,%20Djibril&rft.date=2019-01-01&rft.volume=38&rft.issue=2&rft.spage=173&rft.epage=183&rft.pages=173-183&rft.issn=1580-3139&rft.eissn=1854-5165&rft_id=info:doi/10.5566/ias.2000&rft_dat=%3Cdoaj_cross%3Eoai_doaj_org_article_fc89a8d2903d417c865a8ee8807400db%3C/doaj_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c288t-96c02bbdf223b9b13804f2c45a591d656c9792ddf88e642798922b8ca97932203%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true