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Eminaga O, Ge TJ, Shkolyar E, Laurie MA, Lee TJ, Hockman L, Jia X, Xing L, Liao JC. An Efficient Framework for Video Documentation of Bladder Lesions for Cystoscopy: A Proof-of-Concept Study. J Med Syst 2022; 46:73. [PMID: 36190581 PMCID: PMC10751224 DOI: 10.1007/s10916-022-01862-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 09/07/2022] [Indexed: 10/10/2022]
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.
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Affiliation(s)
- Okyaz Eminaga
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Urology, Stanford University School of Medicine, 453 Quarry Road, Mail Code 5656, Palo Alto, CA, 94304, USA.
| | - T Jessie Ge
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA
| | - Eugene Shkolyar
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA
| | - Mark A Laurie
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA
| | - Timothy J Lee
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA
| | - Lukas Hockman
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA
| | - Xiao Jia
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, USA
| | - Lei Xing
- Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, USA
| | - Joseph C Liao
- Department of Urology, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Urology, Stanford University School of Medicine, 453 Quarry Road, Mail Code 5656, Palo Alto, CA, 94304, USA.
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