Selection of Convolutional Neural Network Model for Bladder Tumor Classification of Cystoscopy Images and Comparison with Humans-Reference-Cited by-同舟云学术

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Selection of Convolutional Neural Network Model for Bladder Tumor Classification of Cystoscopy Images and Comparison with Humans

Published:2024-07-01 Issue: Volume: Page:
ISSN:0892-7790
Container-title:Journal of Endourology
language:en
Short-container-title:Journal of Endourology

Author:

Lee Ju Young¹,Lee Yong Seong²,Tae Jong Hyun³,Chang In Ho³,Kim Tae-Hyoung³,Myung Soon Chul³,Nguyen Tuan Thanh⁴,Lee Jae Hyeok¹,Choi Joongwon²,Kim Jung Hoon²,Kim Jin Wook²,Choi Se Young³

Affiliation:

1. DEEPNOID Inc., Seoul, Korea.

2. Department of Urology, Chung-Ang University Gwangmyeong Hospital, Chung-Ang University College of Medicine, Gyeonggi-do, Korea.

3. Department of Urology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Korea.

4. Department of Urology, Cho Ray Hospital, University of Medicine and Pharmacy, Ho Chi Minh City, Vietnam.

Publisher

Mary Ann Liebert Inc

Link

https://www.liebertpub.com/doi/pdf/10.1089/end.2024.0250

Reference27 articles.

1. Epidemiology of Bladder Cancer

2. Metabolomics of Non-muscle Invasive Bladder Cancer: Biomarkers for Early Detection of Bladder Cancer

3. A review on the accuracy of bladder cancer detection methods

4. Performance of Narrow Band Imaging (NBI) and Photodynamic Diagnosis (PDD) Fluorescence Imaging Compared to White Light Cystoscopy (WLC) in Detecting Non-Muscle Invasive Bladder Cancer: A Systematic Review and Lesion-Level Diagnostic Meta-Analysis

5. Cystoscopic Imaging for Bladder Cancer Detection Based on Stepwise Organic Transfer Learning with a Pretrained Convolutional Neural Network

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