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Innovative computer vision approach to 3D bladder model reconstruction from flexible cystoscopy
Author(s): Nestor Orlando Falcon; Sorush Ranjbar; Exal Cisneros; Bao Vu; Austin Schoppe; Pedro Sanchez; Yufang Jin; JingYong Ye; Yusheng Feng; Dharam Kaushik; R. Lyle Hood
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Paper Abstract

Bladder cancer is the fourth most common cancer in men and is considered to have the highest rate of recurrence of all cancers at ~70%, and transitional cell carcinoma (TCC) is the most common form of intrabladder malignancy. Current standard-of-care for Stages 2 or higher is radical cystectomy, which involves removal of the urinary bladder and nearby lymph nodes. Alternative, organ-sparing treatments such as chemo- or radiotherapy are relatively ineffective against these cancers. The latter is effective when precisely targeted, but suffers from accuracy issues due to low contrast from computed tomography guidance. These motivate an innovative approach to more precisely visualize and spatially pinpoint TCC. This manuscript presents a novel non-invasive computer vision pipeline that can extract 3D structural information from 2D images obtained during routine flexible cystoscopy. The pipeline utilized camera calibration, adaptive thresholding, Scale Invariant Feature Transform (SIFT), and a Structure from Motion (SFM) implementation to reconstruct 3D point clouds of the inner surface of organ phantoms and an ex vivo porcine bladder. 3D point clouds were processed by Poisson reconstruction to generate a textured, triangle meshed 3D surface. The reconstruction pipeline generated a visually recognizable, qualitative 3D representation of the bladder from 2D video captured via flexible cystoscopy. Once further developed, this approach will enhance the targeting precision of external beam radiotherapy, providing clinicians with better organ-sparing methods to treat TCC.

Paper Details

Date Published: 26 February 2019
PDF: 9 pages
Proc. SPIE 10852, Therapeutics and Diagnostics in Urology 2019, 1085207 (26 February 2019); doi: 10.1117/12.2510725
Show Author Affiliations
Nestor Orlando Falcon, The Univ. of Texas at San Antonio (United States)
Sorush Ranjbar, The Univ. of Texas at San Antonio (United States)
Exal Cisneros, The Univ. of Texas at San Antonio (United States)
Bao Vu, The Univ. of Texas at San Antonio (United States)
Austin Schoppe, The Univ. of Texas at San Antonio (United States)
Pedro Sanchez, The Univ. of Texas at San Antonio (United States)
Yufang Jin, The Univ. of Texas at San Antonio (United States)
JingYong Ye, The Univ. of Texas at San Antonio (United States)
Yusheng Feng, The Univ. of Texas at San Antonio (United States)
Dharam Kaushik, The Univ. of Texas at San Antonio (United States)
R. Lyle Hood, The Univ. of Texas at San Antonio (United States)


Published in SPIE Proceedings Vol. 10852:
Therapeutics and Diagnostics in Urology 2019
Hyun Wook Kang, Editor(s)

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