AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Urography

Showing 11 to 17 of 17 articles

Clear Filters

Ga PSMA-11 PET with CT urography protocol in the initial staging and biochemical relapse of prostate cancer.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Ga-labelled prostate specific membrane antigen (PSMA) ligand PET/CT is a promising modality in primary staging (PS) and biochemical relapse (BCR) of prostate cancer (PC). However, pelvic nodes or local recurrences can be difficult to diff...

Integration of CT urography improves diagnostic confidence of Ga-PSMA-11 PET/CT in prostate cancer patients.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: To prove the feasibility of integrating CT urography (CTU) into Ga-PSMA-11 PET/CT and to analyze the impact of CTU on assigning focal tracer accumulation in the ureteric space to either ureteric excretion or metastatic disease concerning ...

Robotic assisted laparoscopic repair of a symptomatic ureterosciatic hernia.

The Canadian journal of urology
Ureterosciatic hernias (USH) are a rare entity and to date there have been limited case reports detailing their presentation, diagnosis, and management. Until recently, repair of ureterosciatic hernias has been performed via open, endoscopic, or pure...

Urinary bladder segmentation in CT urography using deep-learning convolutional neural network and level sets.

Medical physics
PURPOSE: The authors are developing a computerized system for bladder segmentation in CT urography (CTU) as a critical component for computer-aided detection of bladder cancer.

Urinary bladder cancer staging in CT urography using machine learning.

Medical physics
PURPOSE: To evaluate the feasibility of using an objective computer-aided system to assess bladder cancer stage in CT Urography (CTU).

Deep-learning convolutional neural network: Inner and outer bladder wall segmentation in CT urography.

Medical physics
PURPOSE: We are developing a computerized segmentation tool for the inner and outer bladder wall as a part of an image analysis pipeline for CT urography (CTU).

U-Net based deep learning bladder segmentation in CT urography.

Medical physics
OBJECTIVES: To develop a U-Net-based deep learning approach (U-DL) for bladder segmentation in computed tomography urography (CTU) as a part of a computer-assisted bladder cancer detection and treatment response assessment pipeline.