Automatic Segmentation of Pancreatic Tumors Using Deep Learning on a Video Image of Contrast-Enhanced Endoscopic Ultrasound

Automatic Segmentation of Pancreatic Tumors Using Deep Learning on a Video Image of Contrast-Enhanced Endoscopic Ultrasound

Background: Contrast-enhanced endoscopic ultrasound (CE-EUS) is useful for the differentiation of pancreatic tumors. Using deep learning for the segmentation and classification of pancreatic tumors might further improve the diagnostic capability of CE-EUS. Aims: The aim of this study was to evaluate...

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Bibliographic Details
Main Authors: Yuhei Iwasa, Takuji Iwashita, Yuji Takeuchi, Hironao Ichikawa, Naoki Mita, Shinya Uemura, Masahito Shimizu, Yu-Ting Kuo, Hsiu-Po Wang, Takeshi Hara
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Journal of Clinical Medicine
Subjects:
artificial intelligence
pancreatic cancer
endoscopic ultrasound
microbubble
contrast enhanced
Online Access:https://www.mdpi.com/2077-0383/10/16/3589

Internet

https://www.mdpi.com/2077-0383/10/16/3589

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