Automated liver segmentation and steatosis grading using deep learning on B-mode ultrasound images-Reference-Cited by-同舟云学术

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Automated liver segmentation and steatosis grading using deep learning on B-mode ultrasound images

Published:2023-09-03 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Ultrasonics Symposium (IUS)
language:
Short-container-title:

Author:

Vianna Pedro¹,Kulbay Merve¹,Boustros Pamela²,Calce Sara-Ivana¹,Larocque-Rigney Cassandra¹,Patry-Beaudoin Laurent¹,Luo Yi Hui²,Chaudary Muawiz³,Kadoury Samuel¹,Nguyen Bich⁴,Montagnon Emmanuel¹,Belilovsky Eugene³,Wolf Guy³,Chassé Michaël¹,Tang An¹,Cloutier Guy¹

Affiliation:

1. Centre de Recherche du Centre Hospitalier de l'Université de Montréal (CRCHUM),Canada

2. Centre Hospitalier de l’Université de Montréal (CHUM),Département de Radiologie,Canada

3. Mila – Quebec AI Institute,Canada

4. CHUM,Department of Pathology,Canada

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10306337/10306342/10307501.pdf?arnumber=10307501

Reference16 articles.

1. Transfer learning with deep convolutional neural network for liver steatosis assessment in ultrasound images

2. U-Net: Convolutional Networks for Biomedical Image Segmentation;ronneberger;Cham 2015 Springer International Publishing in Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015,0

3. Grzegorz; Szmigielski, Cezary; Kalinowski, Piotr; Michalowski, Lukasz; Paluszkiewicz, Rafal; Ziarkiewicz-Wroblewska, Bogna; Zieniewicz, Krzysztof; Sobieraj, Piotr; Nowicki, Andrzej;byra;Dataset of B-mode fatty liver ultrasound images,0

4. Improving artificial intelligence pipeline for liver malignancy diagnosis using ultrasound images and video frames

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