This scoping review explores the potential of artificial intelligence (AI) in enhancing the
screening, diagnosis, and monitoring of disorders related to body iron levels. A systematic …

Cerebrovascular imaging is a common examination. Its accurate cerebrovascular
segmentation become an important auxiliary method for the diagnosis and treatment of …

Objectives To develop and evaluate a deep convolutional neural network (DCNN) for
automated liver segmentation, volumetry, and radiomic feature extraction on contrast …

Hepatic vessel skeletonization serves as an important means of hepatic vascular analysis
and vessel segmentation. This paper presents a survey of techniques and algorithms for …

Abstract Machine learning and computer vision techniques have grown rapidly in recent
years due to their automation, suitability, and ability to generate astounding results. Hence …

Chronic liver diseases (CLDs) are becoming increasingly more prevalent in modern society.
The use of imaging techniques for early detection, such as magnetic resonance imaging …

Purpose Accurate liver segmentation is key for volumetry assessment to guide treatment
decisions. Moreover, it is an important pre-processing step for cancer detection algorithms …

Accurately measuring the Distance from the lowest boundary of rectal tumor To the Anal
Verge (DTAV) is critical for developing optimal surgical plans for treating patients with rectal …

The role of MRI to estimate liver iron concentration (LIC) for identifying patients with iron
overload and guiding the titration of chelation therapy is increasingly established for routine …

Purpose To develop a fully automatic parenchyma extraction method for the T2* relaxometry
of iron overload liver. Methods A retrospective multicenter collection of liver MR …