Radiology

Latest AI and machine learning research in radiology for healthcare professionals.

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Gray matters: ViT-GAN framework for identifying schizophrenia biomarkers linking structural MRI and functional network connectivity.

Brain disorders are often associated with changes in brain structure and function, where functional ...

Identification of Prolactinoma in Pituitary Neuroendocrine Tumors Using Radiomics Analysis Based on Multiparameter MRI.

This study aims to investigate the feasibility of preoperatively predicting histological subtypes of...

Artificial intelligence-analyzed computed tomography in patients undergoing transcatheter tricuspid valve repair.

BACKGROUND: Baseline right ventricular (RV) function derived from 3-dimensional analyses has been de...

Prediagnosis recognition of acute ischemic stroke by artificial intelligence from facial images.

Stroke is a major threat to life and health in modern society, especially in the aging population. S...

Synergizing Nanomaterials and Artificial Intelligence in Advanced Optical Biosensors for Precision Antimicrobial Resistance Diagnosis.

Antimicrobial resistance (AMR) poses a critical global One Health concern, ensuing from unintentiona...

Causal Forest Machine Learning Analysis of Parkinson's Disease in Resting-State Functional Magnetic Resonance Imaging.

In recent years, Artificial Intelligence has been used to assist healthcare professionals in detecti...

Investigation of Appropriate Scaling of Networks and Images for Convolutional Neural Network-Based Nerve Detection in Ultrasound-Guided Nerve Blocks.

Ultrasound imaging is an essential tool in anesthesiology, particularly for ultrasound-guided periph...

Ultrasound contrast-enhanced radiomics model for preoperative prediction of the tumor grade of clear cell renal cell carcinoma: an exploratory study.

BACKGROUND: This study aims to explore machine learning(ML) methods for non-invasive assessment of W...

Deep learning for colorectal cancer detection in contrast-enhanced CT without bowel preparation: a retrospective, multicentre study.

BACKGROUND: Contrast-enhanced CT scans provide a means to detect unsuspected colorectal cancer. Howe...

Adaptive Knowledge Distillation for High-Quality Unsupervised MRI Reconstruction With Model-Driven Priors.

Magnetic Resonance Imaging (MRI) reconstruction has made significant progress with the introduction ...

Radial Undersampled MRI Reconstruction Using Deep Learning With Mutual Constraints Between Real and Imaginary Components of K-Space.

The deep learning method is an efficient solution for improving the quality of undersampled magnetic...

New liver window width in detecting hepatocellular carcinoma on dynamic contrast-enhanced computed tomography with deep learning reconstruction.

Changing a window width (WW) alters appearance of noise and contrast of CT images. The aim of this s...

Improving intracranial aneurysms image quality and diagnostic confidence with deep learning reconstruction in craniocervical CT angiography.

BACKGROUND: The diagnostic impact of deep learning computed tomography (CT) reconstruction on intrac...

Evaluation of deep-learning TSE images in clinical musculoskeletal imaging.

In this study, we compared the fat-saturated (FS) and non-FS turbo spin echo (TSE) magnetic resonanc...

Spatial and geometric learning for classification of breast tumors from multi-center ultrasound images: a hybrid learning approach.

BACKGROUND: Breast cancer is the most common cancer among women, and ultrasound is a usual tool for ...

Precise positioning of gamma ray interactions in multiplexed pixelated scintillators using artificial neural networks.

. The positioning ofray interactions in positron emission tomography (PET) detectors is commonly mad...

Scan-Specific Self-Supervised Bayesian Deep Non-Linear Inversion for Undersampled MRI Reconstruction.

Magnetic resonance imaging is subject to slow acquisition times due to the inherent limitations in d...

Stitched vision transformer for age-related macular degeneration detection using retinal optical coherence tomography images.

Age-related macular degeneration (AMD) is an eye disease that leads to the deterioration of the cent...

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