Automatic hepatic tumor segmentation in intra-operative ultrasound: a supervised deep-learning approach-Reference-Cited by-同舟云学术

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Automatic hepatic tumor segmentation in intra-operative ultrasound: a supervised deep-learning approach

Published:2024-03-12 Issue:02 Volume:11 Page:
ISSN:2329-4302
Container-title:Journal of Medical Imaging
language:
Short-container-title:J. Med. Imag.

Author:

Natali Tiziano¹,Zhylka Andrey¹,Olthof Karin¹,Smit Jasper N.¹,Baetens Tarik R.¹,Kok Niels F. M.¹,Kuhlmann Koert F. D.¹,Ivashchenko Oleksandra²,Ruers Theo J. M.¹,Fusaglia Matteo¹

Affiliation:

1. The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Department of Surgical Oncology, Amsterdam, The Netherlands

2. University of Groningen, University Medical Center Groningen, Medical Imaging Center, Department of Nuclear Medicine and Molecular Imaging (EB50), Groningen, The Netherlands

Publisher

SPIE-Intl Soc Optical Eng

Reference20 articles.

1. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

2. Ultrasound-based navigation for open liver surgery using active liver tracking

3. Routine Intraoperative Ultrasound for the Detection of Liver Metastases during Resection of Primary Colorectal Cancer – A Systematic Review

4. Ultrasound Based Planning and Navigation for Non-Anatomical Liver Resections – An Ex-Vivo Study

5. Hybrid classification of diffuse liver diseases in ultrasound images using deep convolutional neural networks

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