Automatic pancreas segmentation in contrast enhanced CT data using learned spatial anatomy and texture descriptors-Reference-Cited by-同舟云学术

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Automatic pancreas segmentation in contrast enhanced CT data using learned spatial anatomy and texture descriptors

Published:2011-03 Issue: Volume: Page:
ISSN:
Container-title:2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro
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Author:

Erdt Marius¹,Kirschner Matthias²,Drechsler Klaus¹,Wesarg Stefan²,Hammon Matthias³,Cavallaro Alexander³

Affiliation:

1. Fraunhofer Institute for Computer Graphics Research (IGD), Cognitive Computing & Medical Imaging, Darmstadt, Germany

2. Technische Universitaet Darmstadt, Graphisch-Interaktive Systeme, Germany

3. University Hospital Erlangen, Radiology Institute, Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx5/5783450/5872340/05872821.pdf?arnumber=5872821

Cited by 26 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Reinforcement learning‐based anatomical maps for pancreas subregion and duct segmentation;Medical Physics;2024-07-19

2. LMNS-Net: Lightweight Multiscale Novel Semantic-Net deep learning approach used for automatic pancreas image segmentation in CT scan images;Expert Systems with Applications;2023-12

3. An automatic cascaded approach for pancreas segmentation via an unsupervised localization using 3D CT volumes;Multimedia Systems;2023-05-28

4. RTUNet: Residual transformer UNet specifically for pancreas segmentation;Biomedical Signal Processing and Control;2023-01

5. Pancreas Co-segmentation based on dynamic ROI extraction and VGGU-Net;Expert Systems with Applications;2022-04

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