Hypertension is a major contributor to cardiovascular morbidity and mortality. Its heterogeneity complicates risk stratification. Unsupervised machine learning can uncover risk profiles and refine ...

aDepartment of MRI Center, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, China bDepartment of Radiology Center, The First Affiliated Hospital of Xinxiang Medical ...

This important study uses diffusion magnetic resonance imaging to non-invasively map the white matter fibres connecting the zona incerta and cortex in humans. The authors present convincing evidence ...

We retrospectively analyzed 1,080 nonactionable three-dimensional (3D) reconstructed DBT screening examinations acquired between 2011 and 2016. Reference tissue segmentations were generated using ...

aPrecision Digital Health and Informatics for Life, Clinic of Internal Medicine III, Interdisciplinary Center for Scientific Computing, University of Heidelberg, Heidelberg, Germany bDepartment of ...

Graph-enhanced CNN framework for brain tumor MRI classification using image preprocessing, data augmentation, graph convolution operations, and deep learning techniques for healthcare AI. End-to-end ...

Magnetic resonance imaging (MRI) is invaluable for understanding brain disorders, but data complexity poses a challenge in experimental research. In this study, we introduce suMRak, a MATLAB ...

Segmentation and classification are fundamental tasks in image analysis and computer vision. In addition to having ubiquitous applications in a variety of different fields, segmentation and ...

This study non-invasively investigates blood flow in different regions of the hippocampus using advanced MR imaging techniques in clinically feasible times. The researchers found significant ...