Molecular imaging has experienced enormous advancements in the areas of imaging
technology, imaging probe and contrast development, and data quality, as well as machine …

The high-throughput extraction of quantitative imaging features from medical images for the
purpose of radiomic analysis, ie, radiomics in a broad sense, is a rapidly developing and …

Radiomics refers to the extraction of mineable data from medical imaging and has been
applied within oncology to improve diagnosis, prognostication, and clinical decision support …

The promise of highly personalized oncology care using artificial intelligence (AI)
technologies has been forecasted since the emergence of the field. Cumulative advances …

Background Prediction of microvascular invasion (MVI) may help determine treatment
strategies for hepatocellular carcinoma (HCC). Purpose To develop a radiomics approach …

Background Macrotrabecular-massive (MTM) subtype of hepatocellular carcinoma (HCC) is
an aggressive variant associated with angiogenesis and immunosuppressive tumor …

Filters are commonly used to enhance specific structures and patterns in images, such as
vessels or peritumoral regions, to enable clinical insights beyond the visible image using …

Radiomics is a rapidly developing field of research focused on the extraction of quantitative
features from medical images, thus converting these digital images into minable, high …

Objectives Radiomic features derived from routine medical images show great potential for
personalized medicine in gastric cancer (GC). We aimed to evaluate the current status and …

The development of clinical trials has led to substantial improvements in the prevention and
treatment of many diseases, including brain cancer. Advances in medicine, such as …