Urology

Radiomic Machine Learning: Is It Really a Useful Method for the Characterization of Prostate Cancer?

Exploit fully automatic low-level segmented PET data for training high-level deep learning algorithms for the corresponding CT data.

We present an approach for fully automatic urinary bladder segmentation in CT images with artificial...

Comparison of Artificial Intelligence Techniques to Evaluate Performance of a Classifier for Automatic Grading of Prostate Cancer From Digitized Histopathologic Images.

IMPORTANCE: Proper evaluation of the performance of artificial intelligence techniques in the analys...

U-Net based deep learning bladder segmentation in CT urography.

OBJECTIVES: To develop a U-Net-based deep learning approach (U-DL) for bladder segmentation in compu...

Joint Prostate Cancer Detection and Gleason Score Prediction in mp-MRI via FocalNet.

Multi-parametric MRI (mp-MRI) is considered the best non-invasive imaging modality for diagnosing pr...

A new implementation for online calculation of manipulator Jacobian.

This paper describes a new implementation for calculating Jacobian and its time derivative for robot...

Differentiation of renal angiomyolipoma without visible fat from renal cell carcinoma by machine learning based on whole-tumor computed tomography texture features.

Automatic classification of tissues on pelvic MRI based on relaxation times and support vector machine.

Tissue segmentation and classification in MRI is a challenging task due to a lack of signal intensit...

Machine learning models for predicting post-cystectomy recurrence and survival in bladder cancer patients.

Currently in patients with bladder cancer, various clinical evaluations (imaging, operative findings...

Deeply supervised 3D fully convolutional networks with group dilated convolution for automatic MRI prostate segmentation.

PURPOSE: Reliable automated segmentation of the prostate is indispensable for image-guided prostate ...

Generative Adversarial Networks for Facilitating Stain-Independent Supervised and Unsupervised Segmentation: A Study on Kidney Histology.

A major challenge in the field of segmentation in digital pathology is given by the high effort for ...

Influence of segmentation margin on machine learning-based high-dimensional quantitative CT texture analysis: a reproducibility study on renal clear cell carcinomas.

OBJECTIVE: To determine the possible influence of segmentation margin on each step (feature reproduc...

Differentiating kidney stones from phleboliths in unenhanced low-dose computed tomography using radiomics and machine learning.

OBJECTIVES: Distinguishing between kidney stones and phleboliths can constitute a diagnostic challen...

Development and clinical implementation of SeedNet: A sliding-window convolutional neural network for radioactive seed identification in MRI-assisted radiosurgery (MARS).

PURPOSE: To develop and evaluate a sliding-window convolutional neural network (CNN) for radioactive...

Objective risk stratification of prostate cancer using machine learning and radiomics applied to multiparametric magnetic resonance images.

Multiparametric magnetic resonance imaging (mpMRI) has become increasingly important for the clinica...

Natural language processing to identify ureteric stones in radiology reports.

INTRODUCTION: Natural language processing (NLP) is an emerging tool which has the ability to automat...

Artificial intelligence in cancer imaging: Clinical challenges and applications.

Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered data w...

Dose evaluation of MRI-based synthetic CT generated using a machine learning method for prostate cancer radiotherapy.

Magnetic resonance imaging (MRI)-only radiotherapy treatment planning is attractive since MRI provid...

Argentinian multicenter study on urinary tract infections due to Streptococcus agalactiae in adult patients.

INTRODUCTION: Streptococcus agalactiae (group B streptococcus, GBS) is a recognized urinary pathogen...

A feasibility study for predicting optimal radiation therapy dose distributions of prostate cancer patients from patient anatomy using deep learning.

With the advancement of treatment modalities in radiation therapy for cancer patients, outcomes have...

Editorial Comment to Utility of robot-assisted radical cystectomy with intracorporeal urinary diversion for muscle-invasive bladder cancer.