Computer Vision Enabled Segmentation of Kidney Stones During Ureteroscopy and Laser Lithotripsy-Reference-Cited by-同舟云学术

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Computer Vision Enabled Segmentation of Kidney Stones During Ureteroscopy and Laser Lithotripsy

Published:2023-04-01 Issue:4 Volume:37 Page:495-501
ISSN:0892-7790
Container-title:Journal of Endourology
language:en
Short-container-title:Journal of Endourology

Author:

Setia Shaan A.¹^ORCID,Stoebner Zachary A.²,Floyd Chase³,Lu Daiwei²,Oguz Ipek²,Kavoussi Nicholas L.¹

Affiliation:

1. Department of Urologic Surgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA.

2. Department of Computer Science, Vanderbilt University, Nashville, Tennessee, USA.

3. University of South Carolina School of Medicine, Columbia, South Carolina, USA.

Publisher

Mary Ann Liebert Inc

Subject

Urology

Link

https://www.liebertpub.com/doi/pdf/10.1089/end.2022.0511

Reference17 articles.

1. Pulsed Dye Laser Fragmentation of Ureteral Calculi: Initial Clinical Experience

2. COMPARISON OF FLEXIBLE URETEROSCOPES: DEFLECTION, IRRIGANT FLOW AND OPTICAL CHARACTERISTICS

3. Role of Residual Fragments on the Risk of Repeat Surgery after Flexible Ureteroscopy and Laser Lithotripsy: Single Center Study

4. Deep learning computer vision algorithm for detecting kidney stone composition

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Development of UroSAM: A Machine Learning Model to Automatically Identify Kidney Stone Composition from Endoscopic Video;Journal of Endourology;2024-08-01

2. Automated Upper Tract Urothelial Carcinoma Tumor Segmentation During Ureteroscopy Using Computer Vision Techniques;Journal of Endourology;2024-08-01

3. A machine learning approach using stone volume to predict stone-free status at ureteroscopy;World Journal of Urology;2024-05-22

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