AIMC Topic: Prostate

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Automated multi-modal Transformer network (AMTNet) for 3D medical images segmentation.

Physics in medicine and biology
Over the past years, convolutional neural networks based methods have dominated the field of medical image segmentation. But the main drawback of these methods is that they have difficulty representing long-range dependencies. Recently, the Transform...

Prostatic urinary tract visualization with super-resolution deep learning models.

PloS one
In urethra-sparing radiation therapy, prostatic urinary tract visualization is important in decreasing the urinary side effect. A methodology has been developed to visualize the prostatic urinary tract using post-urination magnetic resonance imaging ...

Computer-aided diagnosis in prostate cancer: a retrospective evaluation of the Watson Elementary system for preoperative tumor characterization in patients treated with robot-assisted radical prostatectomy.

World journal of urology
PURPOSE: Computer-aided diagnosis (CAD) may improve prostate cancer (PCa) detection and support multiparametric magnetic resonance imaging (mpMRI) readers for better characterization. We evaluated Watson Elementary (WE) CAD system results referring t...

Effects of Bladder Neck Plication on Climacturia After Robot-Assisted Laparoscopic Prostatectomy.

Journal of laparoendoscopic & advanced surgical techniques. Part A
The aim of this study is to investigate the effect of bladder neck plication during transperitoneal robot-assisted radical prostatectomy (tRARP) on orgasm-related incontinence (climacturia) and the relationship between International Index of Erectil...

Prostate cancer malignancy detection and localization from mpMRI using auto-deep learning as one step closer to clinical utilization.

Scientific reports
Automatic diagnosis of malignant prostate cancer patients from mpMRI has been studied heavily in the past years. Model interpretation and domain drift have been the main road blocks for clinical utilization. As an extension from our previous work we ...

An ultra-fast deep-learning-based dose engine for prostate VMAT via knowledge distillation framework with limited patient data.

Physics in medicine and biology
. Deep-learning (DL)-based dose engines have been developed to alleviate the intrinsic compromise between the calculation accuracy and efficiency of the traditional dose calculation algorithms. However, current DL-based engines typically possess high...

Estimating diagnostic uncertainty in artificial intelligence assisted pathology using conformal prediction.

Nature communications
Unreliable predictions can occur when an artificial intelligence (AI) system is presented with data it has not been exposed to during training. We demonstrate the use of conformal prediction to detect unreliable predictions, using histopathological d...

A Brief Review of Artificial Intelligence in Genitourinary Oncological Imaging.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Genitourinary (GU) system is among the most commonly involved malignancy sites in the human body. Imaging plays a crucial role not only in diagnosis of cancer but also in disease management and its prognosis. However, interpretation of conventional i...

Predictive factors of de novo overactive bladder in clinically localized prostate cancer patients after robot-assisted radical prostatectomy.

International journal of urology : official journal of the Japanese Urological Association
OBJECTIVES: To assess the postoperative status of clinically localized prostate cancer patients who underwent robot-assisted radical prostatectomy (RARP) with a focus on de novo overactive bladder (OAB).