On evaluating CT image enhancement techniques for deep learning based 3D liver segmentation-Reference-Cited by-同舟云学术

On evaluating CT image enhancement techniques for deep learning based 3D liver segmentation

Published:2022-02-14 Issue: Volume: Page:
ISSN:
Container-title:2022 Global Conference on Wireless and Optical Technologies (GCWOT)
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Author:

Gul Sidra¹,Khan Muhammad Salman²

Affiliation:

1. National Center of Artificial Intelligence, University of Engineering and Technology,Artificial Intelligence in Healthcare, IIPL,Department of Computer Systems Engineering,Peshawar,Pakistan

2. Artificial Intelligence in Healthcare, IIPL, National Center of Artificial Intelligence, University of Engineering and Technology,Qatar University, Doha, Qatar,Department of Electrical Engineering, College of Engineering,Peshawar,Pakistan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9772875/9772876/09772878.pdf?arnumber=9772878

Reference39 articles.

1. The Liver Tumor Segmentation Benchmark (LiTS);bilic;CoRR,2019

2. Use of Spectral Detector Computed Tomography to Improve Liver Segmentation and Volumetry

3. Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields

4. Deep learning of the sectional appearances of 3D CT images for anatomical structure segmentation based on an FCN voting method

5. Brain MR Image Enhancement for Tumor Segmentation Using 3D U-Net

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