The Journal of Urology, 2024
Jonathan E Katz, Jamie Finnegan, Jingpei Lu, Shan Lin, Michael Yip, Roger Sur
Publisher Link: http://journals.lww.com/auajuro/fulltext/2024/05001/pd27_06_3d_rendering_of_cystoscopy_video_footage_.1140.aspx
Abstract: METHODS:With IRB approval we recorded two diagnostic cystoscopies (one with an Ambu disposable flexible cystoscope and the other with a Wolf digital cystoscope). We converted the videos to images and then curated the images to choose approximately 100 images, which minimized blur and spanned a large segment of the bladder. We then utilized the NVIDIA Instant Neural Graphics Primitives (iNGP), a NeRF algorithm that uses multiresolution hash encoding with a compact neural network for significantly faster convergence, to reconstruct the bladder and render novel, unseen views. We computed the structural index similarity (SSIM) and Peak signal to noise ratio (PSNR) to assess the quality and fidelity of the 3D rendering.RESULTS:Both videos were able to be utilized for 3D rendering using iNGP. The rendering derived from the Wolf cystoscopy had a PSNR= 29.8 [min= 27.2, max= 32.6] and SSIM= 0.89 …
Katz et al. (2024) Rendering of Cystoscopy Video Footage: A Novel Method Utilizing Neural Radiance Field Processing, The Journal of Urology, vol. 211, no. 5S, pp. e552.