Radiology

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

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Quantitative image signature and machine learning-based prediction of outcomes in cerebral cavernous malformations.

PURPOSE: There is increasing interest in novel prognostic tools and predictive biomarkers to help id...

A deep-learning approach for segmentation of liver tumors in magnetic resonance imaging using UNet+.

OBJECTIVE: Radiomic and deep learning studies based on magnetic resonance imaging (MRI) of liver tum...

Deep learning system for automated detection of posterior ligamentous complex injury in patients with thoracolumbar fracture on MRI.

This study aimed to develop a deep learning (DL) algorithm for automated detection and localization ...

Fetal biometry and amniotic fluid volume assessment end-to-end automation using Deep Learning.

Fetal biometry and amniotic fluid volume assessments are two essential yet repetitive tasks in fetal...

Prospective assessment of breast lesions AI classification model based on ultrasound dynamic videos and ACR BI-RADS characteristics.

INTRODUCTION: AI-assisted ultrasound diagnosis is considered a fast and accurate new method that can...

Deep Learning-Based Ensembling Technique to Classify Alzheimer's Disease Stages Using Functional MRI.

The major issue faced by elderly people in society is the loss of memory, difficulty learning new th...

Human lower leg muscles grow asynchronously.

Muscle volume must increase substantially during childhood growth to generate the power required to ...

Research related to the diagnosis of prostate cancer based on machine learning medical images: A review.

BACKGROUND: Prostate cancer is currently the second most prevalent cancer among men. Accurate diagno...

Artificial intelligence in interventional pulmonology.

PURPOSE OF REVIEW: In recent years, there has been remarkable progress in the field of artificial in...

India ink to 3D imaging: The legacy of Dr. Deepak "Dee" N. Pandya and his influence on generations of neuroanatomists.

Dr. Deepak "Dee" Pandya spent his career as an internal medicine physician as well as in his respect...

Predicting multiple linear stapler firings in double stapling technique with an MRI-based deep-learning model.

Multiple linear stapler firings is a risk factor for anastomotic leakage (AL) in laparoscopic low an...

Multi-class glioma segmentation on real-world data with missing MRI sequences: comparison of three deep learning algorithms.

This study tests the generalisability of three Brain Tumor Segmentation (BraTS) challenge models usi...

Deep Learning Framework for Liver Segmentation from -Weighted MRI Images.

The human liver exhibits variable characteristics and anatomical information, which is often ambiguo...

Reducing Gadolinium Contrast With Artificial Intelligence.

Gadolinium contrast is an important agent in magnetic resonance imaging (MRI), particularly in neuro...

Development of MRI-Based Deep Learning Signature for Prediction of Axillary Response After NAC in Breast Cancer.

RATIONALE AND OBJECTIVES: To develop a MRI-based deep learning signature for predicting axillary res...

MultiCOVID: a multi modal deep learning approach for COVID-19 diagnosis.

The rapid spread of the severe acute respiratory syndrome coronavirus 2 led to a global overextensio...

Artificial Intelligence-Assisted Sac Diameter Assessment for Complex Endovascular Aortic Repair.

PURPOSE: Artificial intelligence (AI) using an automated, deep learning-based method, Augmented Radi...

Deep learning assisted sparse array ultrasound imaging.

This study aims to restore grating lobe artifacts and improve the image resolution of sparse array u...

Investigating pulse-echo sound speed estimation in breast ultrasound with deep learning.

Ultrasound is an adjunct tool to mammography that can quickly and safely aid physicians in diagnosin...

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