Urology

Shadow-Consistent Semi-Supervised Learning for Prostate Ultrasound Segmentation.

Prostate segmentation in transrectal ultrasound (TRUS) image is an essential prerequisite for many prostate-related clinical procedures, which, however, is also a long-standing problem due to the challenges caused by the low image quality and shadow artifacts. In this paper, we propose a Shadow-consistent Semi-supervised Learning (SCO-SSL) method with two novel mechanisms, namely shadow augmentati...

Improving Medical Images Classification With Label Noise Using Dual-Uncertainty Estimation.

Deep neural networks are known to be data-driven and label noise can have a marked impact on model performance. Recent studies have shown great robustness to classic image recognition even under a high noisy rate. In medical applications, learning from datasets with label noise is more challenging since medical imaging datasets tend to have instance-dependent noise (IDN) and suffer from high obser...

Objective and Subjective Assessment of Bladder Function after Robot-assisted Laparoscopic Radical Hysterectomy for Early-stage Cervical Cancer.

STUDY OBJECTIVE: To examine whether objective bladder function after robot-assisted radical hysterectomy (RRH) for early-stage cervical cancer is corr...

Deep learning body-composition analysis of clinically acquired CT-scans estimates creatinine excretion with high accuracy in patients and healthy individuals.

Assessment of daily creatinine production and excretion plays a crucial role in the estimation of renal function. Creatinine excretion is estimated by...

3D laparoscopic prostatectomy: results of multicentre study.

INTRODUCTION: Three-dimensional laparoscopic prostatectomy (3D LRP) is a potentially cost-effective option for robot-assisted laparoscopic prostatecto...

Sample Size Calculation for Clinical Trials of Medical Decision Support Systems with Binary Outcome.

Currently, software products for use in medicine are actively developed. Among them, the dominant share belongs to clinical decision support systems (...

Are nephrometry scores accurate for the prediction of outcomes in patients with renal angiomyolipoma treated with robot-assisted partial nephrectomy? A multi-institutional analysis.

BACKGROUND: Prediction of complications and surgical outcomes is of outmost importance even in patients with benign renal masses. The aim of our study...

The learning curve for open and minimally-invasive kidney transplantation: a systematic review.

INTRODUCTION: There is lack of evidence on the impact of surgeons' learning curve on postoperative outcomes after open (OKT) or minimally-invasive (ro...

Magnetic-Powered Janus Cell Robots Loaded with Oncolytic Adenovirus for Active and Targeted Virotherapy of Bladder Cancer.

A unique robotic medical platform is designed by utilizing cell robots as the active "Trojan horse" of oncolytic adenovirus (OA), capable of tumor-sel...

Machine learning-based detection of aberrant deep learning segmentations of target and organs at risk for prostate radiotherapy using a secondary segmentation algorithm.

The output of a deep learning (DL) auto-segmentation application should be reviewed, corrected if needed and approved before being used clinically. Th...

Using machine learning techniques to predict antimicrobial resistance in stone disease patients.

PURPOSE: Artificial intelligence is part of our daily life and machine learning techniques offer possibilities unknown until now in medicine. This stu...

Outcomes of Retzius-sparing versus conventional robot-assisted radical prostatectomy: A KSER update series systematic review and meta-analysis.

BACKGROUND: Robotic-assisted radical prostatectomy(RARP) is widely used to surgically treat of localized prostate cancer. Among RARP, retzius-sparing ...

Prediction of the composition of urinary stones using deep learning.

PURPOSE: This study aimed to predict the composition of urolithiasis using deep learning from urinary stone images.

Deep-learning segmentation of ultrasound images for automated calculation of the hydronephrosis area to renal parenchyma ratio.

PURPOSE: We investigated the feasibility of measuring the hydronephrosis area to renal parenchyma (HARP) ratio from ultrasound images using a deep-lea...

Robotic nephroureterectomy in the management of upper tract urothelial cancer: inching toward standard of care?

Upper-tract urothelial carcinoma is a relatively rare malignancy. Current guidelines strongly recommend radical nephroureterectomy with bladder cuff e...

Efficacy of the opened legs position for protecting against postoperative rhabdomyolysis after robot-assisted radical prostatectomy: A propensity score-matched analysis of perioperative outcomes.

OBJECTIVES: The aim of the present study was to clarify the relationships of intraoperative surgical position with the incidence of postoperative rhab...

AI-based optimization for US-guided radiation therapy of the prostate.

OBJECTIVES: Fast volumetric ultrasound presents an interesting modality for continuous and real-time intra-fractional target tracking in radiation the...

Machine Learning-Based Ultrasound Radiomics for Evaluating the Function of Transplanted Kidneys.

The aim of the study described here was to investigate the value of different machine learning models based on the clinical and radiomic features of 2...

Quality of life and secondary outcomes for open versus robot-assisted radical cystectomy: a double-blinded, randomised feasibility trial.

PURPOSE: This study aims to examine quality of life (QoL) before and after radical cystectomy (RC) and compare robot-assisted laparoscopy with intraco...

Validation of a Predictive Model for New Baseline Renal Function After Radical Nephrectomy or Robot-Assisted Partial Nephrectomy in Japanese Patients.

The study's aim was to externally validate a new predictive model for the new baseline glomerular filtration rate (NB-GFR) postnephrectomy among Japa...