Literature DB >> 36190581

An Efficient Framework for Video Documentation of Bladder Lesions for Cystoscopy: A Proof-of-Concept Study.

Okyaz Eminaga1,2, T Jessie Ge3, Eugene Shkolyar3, Mark A Laurie3, Timothy J Lee3, Lukas Hockman3, Xiao Jia4, Lei Xing4, Joseph C Liao5,6.   

Abstract

Processing full-length cystoscopy videos is challenging for documentation and research purposes. We therefore designed a surgeon-guided framework to extract short video clips with bladder lesions for more efficient content navigation and extraction. Screenshots of bladder lesions were captured during transurethral resection of bladder tumor, then manually labeled according to case identification, date, lesion location, imaging modality, and pathology. The framework used the screenshot to search for and extract a corresponding 10-seconds video clip. Each video clip included a one-second space holder with a QR barcode informing the video content. The success of the framework was measured by the secondary use of these short clips and the reduction of storage volume required for video materials. From 86 cases, the framework successfully generated 249 video clips from 230 screenshots, with 14 erroneous video clips from 8 screenshots excluded. The HIPPA-compliant barcodes provided information of video contents with a 100% data completeness. A web-based educational gallery was curated with various diagnostic categories and annotated frame sequences. Compared with the unedited videos, the informative short video clips reduced the storage volume by 99.5%. In conclusion, our framework expedites the generation of visual contents with surgeon's instruction for cystoscopy and potential incorporation of video data towards applications including clinical documentation, education, and research.
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Cystoscopy atlas; Cystoscopy documentation; Data distribution; Data management; Video for cystoscopy; Video-based documentation

Mesh:

Year:  2022        PMID: 36190581     DOI: 10.1007/s10916-022-01862-8

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.920


  16 in total

1.  Diagnostic Classification of Cystoscopic Images Using Deep Convolutional Neural Networks.

Authors:  Okyaz Eminaga; Nurettin Eminaga; Axel Semjonow; Bernhard Breil
Journal:  JCO Clin Cancer Inform       Date:  2018-12

2.  Augmented Bladder Tumor Detection Using Deep Learning.

Authors:  Eugene Shkolyar; Xiao Jia; Timothy C Chang; Dharati Trivedi; Kathleen E Mach; Max Q-H Meng; Lei Xing; Joseph C Liao
Journal:  Eur Urol       Date:  2019-09-17       Impact factor: 20.096

3.  The American Joint Committee on Cancer: the 7th edition of the AJCC cancer staging manual and the future of TNM.

Authors:  Stephen B Edge; Carolyn C Compton
Journal:  Ann Surg Oncol       Date:  2010-06       Impact factor: 5.344

4.  Cystoscopic findings: a video tutorial.

Authors:  Sara M Lenherr; Erin C Crosby; Anne P Cameron
Journal:  Int Urogynecol J       Date:  2015-01-27       Impact factor: 2.894

5.  Artificial Intelligence for Segmentation of Bladder Tumor Cystoscopic Images Performed by U-Net with Dilated Convolution.

Authors:  Jun Mutaguchi; Ken'ichi Morooka; Satoshi Kobayashi; Aiko Umehara; Shoko Miyauchi; Fumio Kinoshita; Junichi Inokuchi; Yoshinao Oda; Ryo Kurazume; Masatoshi Eto
Journal:  J Endourol       Date:  2022-05-17       Impact factor: 2.942

Review 6.  Benign Diseases of the Bladder.

Authors:  Joshua F Coleman; Donna E Hansel
Journal:  Surg Pathol Clin       Date:  2008-12-06

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

Authors:  Atsushi Ikeda; Hirokazu Nosato; Yuta Kochi; Hiromitsu Negoro; Takahiro Kojima; Hidenori Sakanashi; Masahiro Murakawa; Hiroyuki Nishiyama
Journal:  J Endourol       Date:  2020-12-04       Impact factor: 2.942

8.  Presenting an atlas of Hunner lesions in interstitial cystitis which can be identified with office cystoscopy.

Authors:  Carrie Ronstrom; H Henry Lai
Journal:  Neurourol Urodyn       Date:  2020-09-09       Impact factor: 2.696

Review 9.  European Association of Urology Guidelines on Muscle-invasive and Metastatic Bladder Cancer: Summary of the 2020 Guidelines.

Authors:  J Alfred Witjes; Harman Max Bruins; Richard Cathomas; Eva M Compérat; Nigel C Cowan; Georgios Gakis; Virginia Hernández; Estefania Linares Espinós; Anja Lorch; Yann Neuzillet; Mathieu Rouanne; George N Thalmann; Erik Veskimäe; Maria J Ribal; Antoine G van der Heijden
Journal:  Eur Urol       Date:  2020-04-29       Impact factor: 20.096

10.  Support System of Cystoscopic Diagnosis for Bladder Cancer Based on Artificial Intelligence.

Authors:  Atsushi Ikeda; Hirokazu Nosato; Yuta Kochi; Takahiro Kojima; Koji Kawai; Hidenori Sakanashi; Masahiro Murakawa; Hiroyuki Nishiyama
Journal:  J Endourol       Date:  2020-01-14       Impact factor: 2.942

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