OBJECTIVES: Multiple b-value gas diffusion-weighted MRI (DW-MRI) enables non-invasive and quantitative assessment of lung morphometry, but its long acquisition time is not well-tolerated by patients. We aimed to accelerate multiple b-value gas DW-MRI...
OBJECTIVES: To develop and validate a deep learning-based algorithm for segmenting and quantifying the physiological and diseased aorta in computed tomography angiographies.
OBJECTIVES: To evaluate the image quality and iodine concentration (IC) measurements in pancreatic protocol dual-energy computed tomography (DECT) reconstructed using deep learning image reconstruction (DLIR) and compare them with those of images rec...
OBJECTIVE: Assess if deep learning-based artificial intelligence (AI) algorithm improves reader performance for lung cancer detection on chest X-rays (CXRs).
OBJECTIVES: We aimed to assess the performance of radiomics and machine learning (ML) for classification of non-cystic benign and malignant breast lesions on ultrasound images, compare ML's accuracy with that of a breast radiologist, and verify if th...
OBJECTIVES: Although Rolandic epilepsy (RE) has been regarded as a brain developmental disorder, neuroimaging studies have not yet ascertained whether RE has brain developmental delay. This study employed deep learning-based neuroanatomic biomarker t...
OBJECTIVES: Deep learning has been proven to be able to stage liver fibrosis based on contrast-enhanced CT images. However, until now, the algorithm is used as a black box and lacks transparency. This study aimed to provide a visual-based explanation...
• The use of screening breast MRI is expanding beyond high-risk women to include intermediate- and average-risk women.• The study by Pötsch et al uses a radiomics-based method to decrease the number of benign biopsies while maintaining high sensitivi...
OBJECTIVES: To develop a deep learning-based pulmonary vessel segmentation algorithm (DLVS) from noncontrast chest CT and to investigate its clinical implications in assessing vascular remodeling of chronic obstructive lung disease (COPD) patients.
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.