Multi-class motion-based semantic segmentation for ureteroscopy and laser lithotripsy-Reference-Cited by-同舟云学术

Multi-class motion-based semantic segmentation for ureteroscopy and laser lithotripsy

Published:2022-10 Issue: Volume:101 Page:102112
ISSN:0895-6111
Container-title:Computerized Medical Imaging and Graphics
language:en
Short-container-title:Computerized Medical Imaging and Graphics

Author:

Gupta Soumya^ORCID,Ali Sharib^ORCID,Goldsmith Louise^ORCID,Turney Ben^ORCID,Rittscher Jens^ORCID

Funder

Wellcome Trust

Engineering and Physical Sciences Research Council

Boston Scientific Corporation

National Institute for Health and Care Research

Ludwig Institute for Cancer Research

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference49 articles.

1. Kidney stone detection in computed tomography images;Akkasaligar,2017

2. Holmium laser lithotripsy in the new stone age: dust or bust?;Aldoukhi;Front. Surg.,2017

3. Kidney stone disease: an update on current concepts;Alelign;Adv. Urol.,2018

4. Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy;Ali;Med. Image Anal.,2021

5. Conv2Warp: An unsupervised deformable image registration with continuous convolution and warping;Ali,2019

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