Segmenting male pelvic organs from CT images is a prerequisite for prostate cancer radiotherapy. The efficacy of radiation treatment highly depends on segmentation accuracy. However, accurate segmentation of male pelvic organs is challenging due to l...
PURPOSE: Urinary incontinence is a potential side effect of prostatectomy and intensity modulated radiation therapy (IMRT) for prostate cancer. There are limited data on dosimetric parameters that may predict for poor continence recovery in men who r...
OBJECTIVE: To compare the results of traditional laparoscopy and a simple, single-docking robotic approach for retroperitoneal lymph node dissection (RPLND), nephroureterectomy, and bladder cuff excision.
OBJECTIVE: To evaluate urethral catheter (UC) versus suprapubic tube (SPT) without stenting the anastomosis at robot-assisted radical prostatectomy (RALP) regarding surgical outcome and catheter-associated discomfort. One year after surgery, continen...
IEEE transactions on bio-medical engineering
Aug 18, 2015
Diagnosis of lower urinary tract dysfunction with urodynamics has historically relied on data acquired from multiple sensors using nonphysiologically fast cystometric filling. In addition, state-of-the-art neuromodulation approaches to restore bladde...
BACKGROUND: A knowledge-based radiation therapy (KBRT) treatment planning algorithm was recently developed. The purpose of this work is to investigate how plans that are generated with the objective KBRT approach compare to those that rely on the jud...
OBJECTIVES: This study aimed to evaluate the effects of intravesical instillation of the anticholinergic drugs oxybutynin, tolterodine, and trospium on bladder capacity and histopathological changes in the bladder mucosa.
INTRODUCTION: Individuals with spinal cord injury (SCI) have varying bladder health trajectories after their injury. We explored whether a predictive machine learning model could identify which variables impact urinary symptoms.
OBJECTIVE: We aimed to prospectively investigate whether bladder volume measured using deep learning artificial intelligence (AI) algorithms (AI-BV) is more accurate than that measured using conventional methods (C-BV) if using a portable ultrasound ...
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