Novel and powerful 3D adaptive crisp active contour method applied in the segmentation of CT lung images
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- 作者：Pedro Pedrosa Rebouç ; as Filhoa ; pedrosarf@ifce.edu.br" class="auth_mail" title="E-mail the corresponding author ; Paulo Cé ; sar Cortezb ; cortez@lesc.ufc.br" class="auth_mail" title="E-mail the corresponding author ; Antô ; nio C. da Silva Barrosc ; carlosbarros@lapisco.ifce.edu.br" class="auth_mail" title="E-mail the corresponding author ; Victor Hugo C. Albuquerquec ; victor.albuquerque@unifor.br" class="auth_mail" title="E-mail the corresponding author ; Joã ; o Manuel R. S. Tavares ; d ; tavares@fe.up.pt" class="auth_mail" title="E-mail the corresponding author
- 关键词：CT Scan ; Image segmentation ; 3D Reconstruction ; Lung structures
- 刊名：Medical Image Analysis
- 出版年：2017
- 出版时间：January 2017
- 年：2017
- 卷：35
- 期：Complete
- 页码：503-516
- 全文大小：3170 K
文摘
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The 3D Adaptive Crisp Active Contour Method (3D ACACM) is proposed for the segmentation of CT lung images.
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A new 3D adaptive internal energy is defined to optimize the segmentation.
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The automatic initialization of the 3D ACACM is described.
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The 3D ACACM is compared against three methods commonly used in this domain.
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The results confirm the superior effectiveness of the 3D ACACM.