Latest AI and machine learning research in radiology for healthcare professionals.
Virtual clinical trials (VCTs) can be used to evaluate and optimise medical imaging systems. VCTs ar...
Since lung nodules on computed tomography images can have different shapes, contours, textures or lo...
OBJECTIVE: The aim of this study was to evaluate the effect of a deep learning based computer-aided ...
OBJECTIVE: Deep learning (DL) reconstruction enables substantial acceleration of image acquisition w...
Artificial intelligence and machine learning are poised to disrupt PET imaging from bench to clinic....
PET can provide functional images revealing physiologic processes in vivo. Although PET has many app...
High noise and low spatial resolution are two key confounding factors that limit the qualitative and...
Artificial intelligence (AI) techniques for image-based segmentation have garnered much attention in...
The classic prostate cancer (PCa) diagnostic pathway that is based on prostate-specific antigen (PSA...
Radiomics refers to the extraction of mineable data from medical imaging and has been applied within...
Digital medicine has played a vital role in promoting the development of hepatobiliary and pancreati...
A 71-year-old man was referred to our hospital for treatment of a 2 cm-sized right renal mass incide...
Ovarian cancer is one of the three most common gynecological cancers in the world, and is regarded a...
Contrast-enhanced CT is an important method of preoperative diagnosis and evaluation for the malign...
BACKGROUND: The nature of input data is an essential factor when training neural networks. Research ...
The catheterisation laboratory today combines diagnosis and therapeutics, through various imaging mo...
Anastomotic complications occur after 5% to 20% of operations for rectosigmoid colon cancer. The int...
The aim of this work is the preliminary clinical validation and accuracy evaluation of our automatic...
The exploration of three-dimensional chromatin interaction and organization provides insight into me...
Convolutional neural network (CNN) has advanced in recent years and translated from research into me...
BACKGROUND: The prevalence of nonalcoholic fatty liver disease is increasing over time worldwide, wi...