Liver Segmentation in Computed Tomography Images Using Transformers, Inception Module and U-Net-Reference-Cited by-同舟云学术

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Liver Segmentation in Computed Tomography Images Using Transformers, Inception Module and U-Net

Published:2024-04-17 Issue: Volume: Page:199-201
ISSN:
Container-title:2024 10th International Conference on Applied System Innovation (ICASI)
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Author:

Zossou Vincent-Béni Sèna¹,Allodji Rodrigue S.¹,Biaou Olivier²,Ezin Eugène C.³

Affiliation:

1. Université Paris-Saclay, UVSQ, Univ. Paris-Sud, CESP, Équipe Radiation Epidemiology,Villejuif,France

2. CNHU-HKM,Department of Radiology,Cotonou,Benin

3. Institut de Formation et de Recherche en Informatique, University of Abomey-Calavi,Abomey-Calavi,Benin

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10547719/10547721/10547912.pdf?arnumber=10547912

Reference20 articles.

1. Hepatocellular carcinoma

2. A multiple object geometric deformable model for image segmentation

3. A Deep Learning Approach for Liver and Tumor Segmentation in CT Images Using ResUNet

4. Liver tumor segmentation based on 3D convolutional neural network with dual scale

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

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