AIMC Topic: Abdomen

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Robust and efficient abdominal CT segmentation using shape constrained multi-scale attention network.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: Although many deep learning-based abdominal multi-organ segmentation networks have been proposed, the various intensity distributions and organ shapes of the CT images from multi-center, multi-phase with various diseases introduce new challe...

Deep learning based synthetic CT from cone beam CT generation for abdominal paediatric radiotherapy.

Physics in medicine and biology
. Adaptive radiotherapy workflows require images with the quality of computed tomography (CT) for re-calculation and re-optimisation of radiation doses. In this work we aim to improve the quality of on-board cone beam CT (CBCT) images for dose calcul...

Drainless robot-assisted minimally invasive oesophagectomy-randomized controlled trial (RESPECT).

Trials
BACKGROUND: The purpose of this randomized trial is to evaluate the early removal of postoperative drains after robot-assisted minimally invasive oesophagectomy (RAMIE). Evidence is lacking about feasibility, associated pain, recovery, and morbidity.

Adrenal lesion classification with abdomen caps and the effect of ROI size.

Physical and engineering sciences in medicine
Accurate classification of adrenal lesions on magnetic resonance (MR) images are very important for diagnosis and treatment planning. The detection and classification of lesions in medical imaging heavily rely on several key factors, including the sp...

National analysis of cost disparities in robotic-assisted versus laparoscopic abdominal operations.

Surgery
BACKGROUND: Although the use of robotic-assisted surgery continues to expand, the cost-effectiveness of this platform remains unclear. The present study aimed to compare hospitalization costs and clinical outcomes between robotic-assisted surgery and...

Hepatic vessels segmentation using deep learning and preprocessing enhancement.

Journal of applied clinical medical physics
PURPOSE: Liver hepatic vessels segmentation is a crucial step for the diagnosis process in patients with hepatic diseases. Segmentation of liver vessels helps to study the liver internal segmental anatomy that helps in the preoperative planning of su...

Technical Advancements in Abdominal Diffusion-weighted Imaging.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
Since its first observation in the 18th century, the diffusion phenomenon has been actively studied by many researchers. Diffusion-weighted imaging (DWI) is a technique to probe the diffusion of water molecules and create a MR image with contrast bas...

Deep Learning-Based Computed Tomography Image Standardization to Improve Generalizability of Deep Learning-Based Hepatic Segmentation.

Korean journal of radiology
OBJECTIVE: We aimed to investigate whether image standardization using deep learning-based computed tomography (CT) image conversion would improve the performance of deep learning-based automated hepatic segmentation across various reconstruction met...