{"title":"Virtual simulator for cystoscopy containing motion blur and bladder debris to aid the development of clinical tools.","authors":"Rachel Eimen, Kristen R Scarpato, Audrey K Bowden","doi":"10.1364/BOE.539741","DOIUrl":null,"url":null,"abstract":"<p><p>Cystoscopic data can be used to improve bladder cancer care, but cystoscopic videos are cumbersome to review. Alternatively, cystoscopic video data can be preserved in the form of a 3D bladder reconstruction, which is both informative and convenient to review. Developing algorithms for 3D reconstruction is an iterative process and often requires access to clinical data. Unfortunately, the time and access constraints of the urology clinical workflow can inhibit this technical development. In this manuscript, we present a virtual cystoscopy simulator to enable the creation of realistic and customizable cystoscopy videos through the inclusion of motion blur and bladder debris. The user can induce motion blur at set points in the video by setting the cystoscope speed between 1 and 9 cm/s. We also introduce 12 models of bladder debris particles, each model of which has a different color, shape, or size. The user can add bladder debris to the virtual bladder by specifying which debris models to include, the density of the particles, defining the number of particles in the bladder, and whether debris is stationary or blurred and moving at a user-defined speed. This simulator can be used to generate a large collection of unique and realistic cystoscopy videos with characteristics defined by the user for their specific purpose, thereby assisting the development of novel technologies for clinical implementation.</p>","PeriodicalId":8969,"journal":{"name":"Biomedical optics express","volume":"15 11","pages":"6228-6241"},"PeriodicalIF":2.9000,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11563326/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biomedical optics express","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1364/BOE.539741","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/11/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
Cystoscopic data can be used to improve bladder cancer care, but cystoscopic videos are cumbersome to review. Alternatively, cystoscopic video data can be preserved in the form of a 3D bladder reconstruction, which is both informative and convenient to review. Developing algorithms for 3D reconstruction is an iterative process and often requires access to clinical data. Unfortunately, the time and access constraints of the urology clinical workflow can inhibit this technical development. In this manuscript, we present a virtual cystoscopy simulator to enable the creation of realistic and customizable cystoscopy videos through the inclusion of motion blur and bladder debris. The user can induce motion blur at set points in the video by setting the cystoscope speed between 1 and 9 cm/s. We also introduce 12 models of bladder debris particles, each model of which has a different color, shape, or size. The user can add bladder debris to the virtual bladder by specifying which debris models to include, the density of the particles, defining the number of particles in the bladder, and whether debris is stationary or blurred and moving at a user-defined speed. This simulator can be used to generate a large collection of unique and realistic cystoscopy videos with characteristics defined by the user for their specific purpose, thereby assisting the development of novel technologies for clinical implementation.
期刊介绍:
The journal''s scope encompasses fundamental research, technology development, biomedical studies and clinical applications. BOEx focuses on the leading edge topics in the field, including:
Tissue optics and spectroscopy
Novel microscopies
Optical coherence tomography
Diffuse and fluorescence tomography
Photoacoustic and multimodal imaging
Molecular imaging and therapies
Nanophotonic biosensing
Optical biophysics/photobiology
Microfluidic optical devices
Vision research.