AIMC Topic: Prostate

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Robot-assisted radical prostatectomy training: Description of a canine cadaveric model.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Assess the relevance of a canine model in robot-assisted radical prostatectomy (RARP) training.

Robot-Assisted Simple Prostatectomy Endoscopic Enucleation of the Prostate: A Systematic Review and Meta-Analysis of Comparative Trials.

Journal of endourology
Robot-assisted simple prostatectomy (RASP) and endoscopic enucleation of the prostate (EEP) are two minimally invasive alternatives to simple prostatectomy, which is considered the standard treatment in large prostate glands. It remains unclear whic...

Deep Learning Reconstruction of Diffusion-weighted MRI Improves Image Quality for Prostatic Imaging.

Radiology
Background Deep learning reconstruction (DLR) may improve image quality. However, its impact on diffusion-weighted imaging (DWI) of the prostate has yet to be assessed. Purpose To determine whether DLR can improve image quality of diffusion-weighted ...

Deep learning-based artificial intelligence for prostate cancer detection at biparametric MRI.

Abdominal radiology (New York)
PURPOSE: To present fully automated DL-based prostate cancer detection system for prostate MRI.

Does type of robotic platform make a difference in the final cost of robotic-assisted radical prostatectomy?

Journal of robotic surgery
This study evaluates the difference of robot-assisted radical prostatectomy (RARP) costs in patients with similar preoperative characteristics operated on using the da Vinci SP and Xi robotic platforms. We performed a retrospective analysis on 71 con...

Weakly supervised segmentation with cross-modality equivariant constraints.

Medical image analysis
Weakly supervised learning has emerged as an appealing alternative to alleviate the need for large labeled datasets in semantic segmentation. Most current approaches exploit class activation maps (CAMs), which can be generated from image-level annota...