AIMC Topic: Urinary Bladder

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Using multi-layer perceptron with Laplacian edge detector for bladder cancer diagnosis.

Artificial intelligence in medicine
In this paper, the urinary bladder cancer diagnostic method which is based on Multi-Layer Perceptron and Laplacian edge detector is presented. The aim of this paper is to investigate the implementation possibility of a simpler method (Multi-Layer Per...

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...

Robot-assisted laparoscopic augmentation ileocystoplasty and excision of an intraperitoneal mass: a case report.

The Journal of international medical research
OBJECTIVE: This case is reported to introduce an advanced surgical technique and share our experience with surgeons.

CT male pelvic organ segmentation using fully convolutional networks with boundary sensitive representation.

Medical image analysis
Accurate segmentation of the prostate and organs at risk (e.g., bladder and rectum) in CT images is a crucial step for radiation therapy in the treatment of prostate cancer. However, it is a very challenging task due to unclear boundaries, large intr...

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

PloS one
We present an approach for fully automatic urinary bladder segmentation in CT images with artificial neural networks in this study. Automatic medical image analysis has become an invaluable tool in the different treatment stages of diseases. Especial...