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Automatic thoracic anatomy segmentation on CT images using hierarchical fuzzy models and registration

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成果类型:
期刊论文
作者:
Sun, Kaiqiong*;Udupa, Jayaram K.;Odhner, Dewey;Tong, Yubing;Zhao, Liming;...
通讯作者:
Sun, Kaiqiong
作者机构:
[Sun, Kaiqiong] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430023, Peoples R China.
[Tong, Yubing; Zhao, Liming; Udupa, Jayaram K.; Odhner, Dewey; Torigian, Drew A.] Univ Penn, Dept Radiol, Med Image Proc Grp, Philadelphia, PA 19104 USA.
[Zhao, Liming] Chongqing Univ Posts & Telecommun, Res Ctr Intelligent Syst & Robot, Chongqing 400065, Peoples R China.
通讯机构:
[Sun, Kaiqiong] W
Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430023, Peoples R China.
语种:
英文
关键词:
biological organs;computerised tomography;fuzzy set theory;image recognition;image registration;image segmentation;medical image processing;object recognition;physiological models;Computed tomography;Segmentation;Registration;Computerised tomographs;Biological material, e.g. blood, urine;Haemocytometers;Digital computing or data processing equipment or methods, specially adapted for specific applications;Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints;Image data processing or generation, in general;shape modeling;fuzzy models;object recognition;fuzzy connectedness;segmentation;registration;Ion-mobility spectrometry;Computed tomography;Lungs;Medical image segmentation;Data sets;Computer modeling;Collective models;Biomedical modeling
期刊:
Medical Physics
ISSN:
0094-2405
年:
2016
卷:
43
期:
3
页码:
1487-1500
基金类别:
National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61163046]
机构署名:
本校为第一且通讯机构
院系归属:
数学与计算机学院
摘要:
Purpose: In an attempt to overcome several hurdles that exist in organ segmentation approaches, the authors previously described a general automatic anatomy recognition (AAR) methodology for segmenting all major organs in multiple body regions body-wide [J. K. Udupa et al., "Body-wide hierarchical fuzzy modeling, recognition, and delineation of anatomy in medical images,"Med. Image Anal. 18(5), 752-771 (2014)]. That approach utilized fuzzy modeling strategies, a hierarchical organization of organs, and divided the segmentation task into a recognition step to localize organs which was then foll...

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