Improved Pancreas Segmentation using Multiple Concatenated U-Net Model for Medical Image Systems-Reference-Cited by-同舟云学术

Improved Pancreas Segmentation using Multiple Concatenated U-Net Model for Medical Image Systems

Published:2022-05-31 Issue:5 Volume:20 Page:81-87
ISSN:1598-8619
Container-title:The Journal of Korean Institute of Information Technology
language:en
Short-container-title:jkiit

Author:

Lee Sang-Min^ORCID,Lee Sang-Yun^ORCID,Kim Namgi^ORCID

Funder

Gyeonggi-do Regional Research Center

Publisher

Korean Institute of Information Technology

Reference14 articles.

1. Nuclei Segmentation with Recurrent Residual Convolutional Neural Networks based U-Net (R2U-Net)

2. L. Li, M. Verma, Y. Nakashima, H. Nagahara, and R. Kawasaki, "IterNet: Retinal Image Segmentation Utilizing Structural Redundancy in Vessel Networks", IEEE/CVF Winter Conference on Applications of Computer Vision, pp. 3656-3665, 2020.

3. U-Net: Convolutional Networks for Biomedical Image Segmentation

4. O. Oktay, J. Schlemper, L. L. Folgoc, M. Lee, M. Heinrich, K. Misawa, and D. Rueckert, "Attention U-net: Learning Where to Look for the Pancreas", arXiv preprint arXiv:1804.03999, 2018.

5. Q. Yu, L. Xie, Y. Wang, Y. Zhou, E. K. Fishman, and A. L. Yuille, "Recurrent Saliency Transformation Network: Incorporating Multi-stage Visual Cues for Small Organ Segmentation", IEEE Conference on Computer Vision and Pattern Recognition, 2018.

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