消息
×
loading..
Morphology-Guided Prostate MRI Segmentation with Multi-slice Association
2021-07-01
会议录名称LECTURE NOTES IN COMPUTER SCIENCE (IF:0.402[JCR-2005],0.000[5-Year])
ISSN0302-9743
卷号12966 LNCS
页码507-516
发表状态已发表
DOI10.1007/978-3-030-87589-3_52
摘要

Prostate segmentation from magnetic resonance (MR) images plays an important role in prostate cancer diagnosis and treatment. Previous works typically overlooked large variations of prostate shapes, especially on the boundary area. Furthermore, the small glandular areas at ending slices also make the task very challenging. To overcome these problems, this paper presents a two-stage framework that explicitly utilizes prostate morphological representations (e.g., point, boundary) to accurately localize the prostate region with a coarse volumetric segmentation. Based on the 3D coarse outputs of the first stage, a 2D segmentation network with multi-slice association is further introduced to produce more reliable and accurate segmentation, due to large slice thickness in prostate MR images. Besides, several novel loss functions are further designed to enhance the consistency of prostate boundaries. Extensive experiments on large prostate MRI dataset show superior performance of our proposed method compared to several state-of-the-art methods. © 2021, Springer Nature Switzerland AG.

关键词Diagnosis Diseases Image segmentation Large dataset Magnetic resonance Magnetic resonance imaging Medical imaging Morphology 2D segmentation Cancer diagnosis Morphological representation MRI segmentation Multi slices Multi slice association Prostate cancers Prostate MRI segmentation Prostate segmentation Volumetric segmentations
会议名称12th International Workshop on Machine Learning in Medical Imaging, MLMI 2021, held in conjunction with 24th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2021
会议地点Virtual, Online
会议日期September 27, 2021 - September 27, 2021
收录类别EI
语种英语
出版者Springer Science and Business Media Deutschland GmbH
EI入藏号20214110990346
EI主题词Urology
EISSN1611-3349
EI分类号461.1 Biomedical Engineering ; 461.6 Medicine and Pharmacology ; 701.2 Magnetism: Basic Concepts and Phenomena ; 723.2 Data Processing and Image Processing ; 746 Imaging Techniques ; 931.2 Physical Properties of Gases, Liquids and Solids ; 951 Materials Science
原始文献类型Conference article (CA)
引用统计
正在获取...
文献类型会议论文
条目标识符https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/133493
专题信息科学与技术学院_本科生
生物医学工程学院_PI研究组_沈定刚组
通讯作者Feng, Jun
作者单位
1.School of Information Science and Technology, Northwest University, Xi’an, China;
2.Department of Computer Science, The University of Hong Kong, Hong Kong;
3.School of Electrical and Information Engineering, Shandong University, Weihai, China;
4.School of Computer Science and Engineering, Northwestern Polytechnical University, Xi’an, China;
5.Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China;
6.School of Biomedical Engineering, ShanghaiTech University, Shanghai, China
推荐引用方式
GB/T 7714
Li, Jianping,Cui, Zhiming,Wang, Shuai,et al. Morphology-Guided Prostate MRI Segmentation with Multi-slice Association[C]:Springer Science and Business Media Deutschland GmbH,2021:507-516.
条目包含的文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
个性服务
查看访问统计
谷歌学术
谷歌学术中相似的文章
[Li, Jianping]的文章
[Cui, Zhiming]的文章
[Wang, Shuai]的文章
百度学术
百度学术中相似的文章
[Li, Jianping]的文章
[Cui, Zhiming]的文章
[Wang, Shuai]的文章
必应学术
必应学术中相似的文章
[Li, Jianping]的文章
[Cui, Zhiming]的文章
[Wang, Shuai]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。