AIMC Topic: Urinary Bladder

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Robotic soft swim bladder using liquid-vapor phase transition.

Materials horizons
The swim bladder is crucial to underwater robots to enhance their overall performance and to expand their range of motion. However, previous attempts to incorporate this function have failed or have adopted mechanical swim bladders with high-disturba...

Preoperative Bladder Bowel Dysfunction Is the Most Important Predictive Factor for Postoperative Urinary Retention After Robot-Assisted Laparoscopic Ureteral Reimplantation via An Extravesical Approach: A Multi-Center Study.

Journal of endourology
Postoperative acute urinary retention (pAUR) is a known occurrence after robot-assisted laparoscopic ureteral reimplantation via an extravesical approach (RALUR-EV). We hypothesized that the risk factor of pAUR after RALUR-EV might be similar to tha...

[Urethro-vesical anastomosis reconstruction using extra-peritoneal robot-assisted laparoscopy for anastomotic stenosis after radical prostatectomy].

Progres en urologie : journal de l'Association francaise d'urologie et de la Societe francaise d'urologie
INTRODUCTION: Urethro-vesical anastomosis stenosis following radical prostatectomy is a rare complication but represents a challenging situation. While the first-line treatment is endoscopic, recurrences after urethrotomies require a radical approach...

Validation of the Khorana Score for Prediction of Venous Thromboembolism After Robot-Assisted Radical Cystectomy.

Journal of endourology
The Khorana score (KS) is used to predict the risk of venous thromboembolism (VTE) for cancer patients. We sought to assess the association between KS and VTE for patients who underwent robot-assisted radical cystectomy (RARC). We reviewed our pros...

A deep neural network for estimating the bladder boundary using electrical impedance tomography.

Physiological measurement
OBJECTIVE: Accurate bladder size estimation is an important clinical parameter that assists physicians, enabling them to provide better treatment for patients who are suffering from urinary incontinence. Electrical impedance tomography (EIT) is a non...

CT-ORG, a new dataset for multiple organ segmentation in computed tomography.

Scientific data
Despite the relative ease of locating organs in the human body, automated organ segmentation has been hindered by the scarcity of labeled training data. Due to the tedium of labeling organ boundaries, most datasets are limited to either a small numbe...

Network-based machine learning in colorectal and bladder organoid models predicts anti-cancer drug efficacy in patients.

Nature communications
Cancer patient classification using predictive biomarkers for anti-cancer drug responses is essential for improving therapeutic outcomes. However, current machine-learning-based predictions of drug response often fail to identify robust translational...

Machine Segmentation of Pelvic Anatomy in MRI-Assisted Radiosurgery (MARS) for Prostate Cancer Brachytherapy.

International journal of radiation oncology, biology, physics
PURPOSE: To investigate machine segmentation of pelvic anatomy in magnetic resonance imaging (MRI)-assisted radiosurgery (MARS) for prostate cancer using prostate brachytherapy MRIs acquired with different pulse sequences and image contrasts.

Clinical Evaluation of Deep Learning and Atlas-Based Auto-Contouring of Bladder and Rectum for Prostate Radiation Therapy.

Practical radiation oncology
PURPOSE: Auto-contouring may reduce workload, interobserver variation, and time associated with manual contouring of organs at risk. Manual contouring remains the standard due in part to uncertainty around the time and workload savings after accounti...

Automatic segmentation of pelvic organs-at-risk using a fusion network model based on limited training samples.

Acta oncologica (Stockholm, Sweden)
Efficient and accurate methods are needed to automatically segmenting organs-at-risk (OAR) to accelerate the radiotherapy workflow and decrease the treatment wait time. We developed and evaluated the use of a fused model Dense V-Network for its abil...