The international journal of medical robotics + computer assisted surgery : MRCAS
Oct 25, 2022
BACKGROUND: Magnetic resonance imaging (MRI)-guided biopsies are an accurate, but technically challenging, method for screening and diagnosis of breast lesions. This study assesses the safety and efficacy of an Image Guided Automated Robot (IGAR) in ...
PURPOSE: Prostate biparametric magnetic resonance imaging (bpMRI) including T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) might be an alternative to multiparametric MRI (mpMRI, including dynamic contrast imaging, DCE) to detect and ...
OBJECTIVES: To evaluate the effect of a deep learning-based computer-aided diagnosis (DL-CAD) system on experienced and less-experienced radiologists in reading prostate mpMRI.
OBJECTIVES: The aim of this study was to estimate the prospective utility of a previously retrospectively validated convolutional neural network (CNN) for prostate cancer (PC) detection on prostate magnetic resonance imaging (MRI).
INTRODUCTION: The ReIMAGINE Consortium was conceived to develop risk-stratification models that might incorporate the full range of novel prostate cancer (PCa) diagnostics (both commercial and academic).
AIMS: We evaluated the performance of contrast-enhanced ultrasound (CEUS) based on radiomics analysis to distinguish benign from malignant breast masses.
Prostate cancer (PCa) is the most common cancer type in males in the Western World. MRI has an established role in diagnosis of PCa through guiding biopsies. Due to multistep complex nature of the MRI-guided PCa diagnosis pathway, diagnostic performa...
Medical & biological engineering & computing
Nov 23, 2021
A transurethral prostate biopsy device is proposed in this paper, which can shoot a biopsy needle at different angles to take samples from multiple locations within the prostate. Firstly, the traditional prostate biopsy methods, including transrectal...
OBJECTIVES: To assess Prostate Imaging Reporting and Data System (PI-RADS)-trained deep learning (DL) algorithm performance and to investigate the effect of data size and prior knowledge on the detection of clinically significant prostate cancer (csP...
BACKGROUND: Due to the low cancer-detection rate in patients with PIRADS category 3 lesions, we created machine learning (ML) models to facilitate decision-making about whether to perform prostate biopsies or monitor clinical information without biop...
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