AIMC Topic: Prostatic Neoplasms

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Comparison of Deep Learning-Based and Patch-Based Methods for Pseudo-CT Generation in MRI-Based Prostate Dose Planning.

International journal of radiation oncology, biology, physics
PURPOSE: Deep learning methods (DLMs) have recently been proposed to generate pseudo-CT (pCT) for magnetic resonance imaging (MRI) based dose planning. This study aims to evaluate and compare DLMs (U-Net and generative adversarial network [GAN]) usin...

Growth Inhibitory and Pro-Apoptotic Effects of Ornamental Pomegranate Extracts in Du145 Human Prostate Cancer Cells.

Nutrition and cancer
Prostate cancer is the most common form of cancer in the male. Epidemiological studies have associated increased cancer incidence with reduced consumption of fruit and vegetables. This study was aimed to investigate the influence of dwarf pomegranat...

A deep learning method for image-based subject-specific local SAR assessment.

Magnetic resonance in medicine
PURPOSE: Local specific absorption rate (SAR) cannot be measured and is usually evaluated by offline numerical simulations using generic body models that of course will differ from the patient's anatomy. An additional safety margin is needed to inclu...

Characteristics of urodynamic study parameters associated with intermediate-term continence after robot-assisted radical prostatectomy in elderly patients.

The aging male : the official journal of the International Society for the Study of the Aging Male
PURPOSE: To investigate the relationship between urodynamic study (UDS) data and recovery of urinary incontinence (UI) in elderly patients who underwent robot-assisted radical prostatectomy (RARP).

Semi-automatic classification of prostate cancer on multi-parametric MR imaging using a multi-channel 3D convolutional neural network.

European radiology
OBJECTIVE: To present a deep learning-based approach for semi-automatic prostate cancer classification based on multi-parametric magnetic resonance (MR) imaging using a 3D convolutional neural network (CNN).

A machine learning-assisted decision-support model to better identify patients with prostate cancer requiring an extended pelvic lymph node dissection.

BJU international
OBJECTIVES: To develop a machine learning (ML)-assisted model to identify candidates for extended pelvic lymph node dissection (ePLND) in prostate cancer by integrating clinical, biopsy, and precisely defined magnetic resonance imaging (MRI) findings...

Hospital readmissions after limited vs. extended lymph node dissection during open and robot-assisted radical prostatectomy.

Urologic oncology
PURPOSE: Differences exist concerning when and how to perform lymph node dissection (LND) during radical prostatectomy due to lack of high-grade evidence to its safety and efficacy. We aimed to compare readmission rates between limited and extended L...

Learning to detect lymphocytes in immunohistochemistry with deep learning.

Medical image analysis
The immune system is of critical importance in the development of cancer. The evasion of destruction by the immune system is one of the emerging hallmarks of cancer. We have built a dataset of 171,166 manually annotated CD3 and CD8 cells, which we us...

Encoder-decoder with dense dilated spatial pyramid pooling for prostate MR images segmentation.

Computer assisted surgery (Abingdon, England)
Automatic segmentation of prostate magnetic resonance (MR) images has great significance for the diagnosis and clinical application of prostate diseases. It faces enormous challenges because of the low contrast of the tissue boundary and the small ef...