Comparison of semi-automatic and deep learning-based automatic methods for liver segmentation in living liver transplant donors-Reference-Cited by-同舟云学术

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Comparison of semi-automatic and deep learning-based automatic methods for liver segmentation in living liver transplant donors

Published:2020-01-02 Issue:1 Volume:26 Page:11-21
ISSN:1305-3612
Container-title:Diagnostic and Interventional Radiology
language:
Short-container-title:Diagn Interv Radiol

Author:

Kavur A. Emre, ,Gezer Naciye Sinem,Baris Mustafa,Sahin Yusuf,Ozkan Savas,Baydar Bora,Yuksel Ulas,Kilikcier Caglar,Olut Sahin,Bozdagi Akar Gozde,Unal Gozde,Dicle Oguz,Selver M. Alper, , , , , , , , , , , ,

Publisher

AVES Publishing Co.

Subject

Cardiology and Cardiovascular Medicine,Radiology, Nuclear Medicine and imaging

Cited by 59 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. Cross-Modal Learning via Adversarial Loss and Covariate Shift for Enhanced Liver Segmentation;IEEE Transactions on Emerging Topics in Computational Intelligence;2024-08

2. A data augmentation approach that ensures the reliability of foregrounds in medical image segmentation;Image and Vision Computing;2024-07

3. Evaluation of Various Methods of Liver Measurement in Comparison to Volumetric Segmentation Based on Computed Tomography;Journal of Clinical Medicine;2024-06-21

4. Customized m-RCNN and hybrid deep classifier for liver cancer segmentation and classification;Heliyon;2024-05

5. Pre-operative assessment of living liver donors’ liver anatomy and volumes;Updates in Surgery;2024-03-25

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