Automatic detection of pleural effusion in chest radiographs
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- 作者：Pragnya Maduskar ; pragnya.m@gmail.com" class="auth_mail" title="E-mail the corresponding author ; pragnya.maduskar@radboudumc.nl" class="auth_mail" title="E-mail the corresponding author ; Rick H.M.M. Philipsen rick.philipsen@radboudumc.nl" class="auth_mail" title="E-mail the corresponding author ; Jaime Melendez jaime.melendezrodriguez@radboudumc.nl" class="auth_mail" title="E-mail the corresponding author ; Ernst Scholten ernst.scholten@radboudumc.nl" class="auth_mail" title="E-mail the corresponding author ; Duncan Chanda duncanchanda@gmail.com" class="auth_mail" title="E-mail the corresponding author ; Helen Ayles Helen@zambart.org.zm" class="auth_mail" title="E-mail the corresponding author ; Clara I. Sá ; nchez clara.sanchezgutierrez@radboudumc.nl" class="auth_mail" title="E-mail the corresponding author ; Bram van Ginneken bram.vanginneken@radboudumc.nl" class="auth_mail" title="E-mail the corresponding author
- 关键词：Automated ; Computer-aided detection (CAD) ; Pleural fluid ; Tuberculosis ; Costophrenic angle
- 刊名：Medical Image Analysis
- 出版年：2016
- 出版时间：February 2016
- 年：2016
- 卷：28
- 期：Complete
- 页码：22-32
- 全文大小：4261 K
文摘
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Proposed and evaluated a novel CAD system for pleural effusion detection on 638 chest radiographs.
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A robust way to localize the costophrenic region using chest wall contour as a landmark structure, in addition to the lung segmentation is introduced.
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Additional region descriptors are proposed based on intensity and morphology information in the region around the costophrenic recess.
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Superior results are achieved compared to prior work with AUC values of 0.84 and 0.90 for the left and right pleural effusion detection, respectively.