Radiology

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

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MR-Transformer: A Vision Transformer-based Deep Learning Model for Total Knee Replacement Prediction Using MRI.

Purpose To develop a transformer-based deep learning model-MR-Transformer-that leverages ImageNet p...

Late gadolinium enhancement imaging and sudden cardiac death.

The prediction and management of sudden cardiac death risk continue to pose significant challenges i...

Radiology and the Innovator's Dilemma: Is Disruption on the Horizon?

Radiology is experiencing a growing workforce shortage, presenting opportunity for disruption by non...

A literature review of radio-genomics in breast cancer: Lessons and insights for low and middle-income countries.

To improve precision medicine in breast cancer (BC) decision-making, radio-genomics is an emerging b...

An interpretable machine learning model for predicting bone marrow invasion in patients with lymphoma via F-FDG PET/CT: a multicenter study.

PURPOSE: Accurate identification of bone marrow invasion (BMI) is critical for determining the progn...

F-FDG PET-based liver segmentation using deep-learning.

Organ segmentation using F-FDG PET images alone has not been extensively explored. Segmentation base...

Comparison of diagnostic performance between manual diagnosis following PROMISE V2 and aPROMISE utilizing Ga/F-PSMA PET/CT.

BACKGROUNDS: Automated PROMISE (aPROMISE), which is an artificial intelligence-supported software fo...

Advanced finite segmentation model with hybrid classifier learning for high-precision brain tumor delineation in PET imaging.

Brain tumor segmentation plays a crucial role in clinical diagnostics and treatment planning, yet ac...

Fetal-Net: enhancing Maternal-Fetal ultrasound interpretation through Multi-Scale convolutional neural networks and Transformers.

Ultrasound imaging plays an important role in fetal growth and maternal-fetal health evaluation, but...

Deep Learning for Osteoporosis Diagnosis Using Magnetic Resonance Images of Lumbar Vertebrae.

This work uses T1, STIR, and T2 MRI sequences of the lumbar vertebrae and BMD measurements to identi...

Motion artifacts and image quality in stroke MRI: associated factors and impact on AI and human diagnostic accuracy.

OBJECTIVES: To assess the prevalence of motion artifacts and the factors associated with them in a c...

Preoperative prediction value of 2.5D deep learning model based on contrast-enhanced CT for lymphovascular invasion of gastric cancer.

To develop and validate artificial intelligence models based on contrast-enhanced CT(CECT) images of...

Poincare guided geometric UNet for left atrial epicardial adipose tissue segmentation in Dixon MRI images.

Epicardial Adipose Tissue (EAT) is a recognized risk factor for cardiovascular diseases and plays a ...

Advancing Early Detection of Major Depressive Disorder Using Multisite Functional Magnetic Resonance Imaging Data: Comparative Analysis of AI Models.

BACKGROUND: Major depressive disorder (MDD) is a highly prevalent mental health condition with signi...

Bayesian Posterior Distribution Estimation of Kinetic Parameters in Dynamic Brain PET Using Generative Deep Learning Models.

Positron Emission Tomography (PET) is a valuable imaging method for studying molecular-level process...

3D isotropic high-resolution fetal brain MRI reconstruction from motion corrupted thick data based on physical-informed unsupervised learning.

High-quality 3D fetal brain MRI reconstruction from motion-corrupted 2D slices is crucial for precis...

Placenta segmentation redefined: review of deep learning integration of magnetic resonance imaging and ultrasound imaging.

Placental segmentation is critical for the quantitative analysis of prenatal imaging applications. H...

Vision transformer and complex network analysis for autism spectrum disorder classification in T1 structural MRI.

BACKGROUND: Autism spectrum disorder (ASD) affects social interaction, communication, and behavior. ...

Assessment of local recurrence risk in extremity high-grade osteosarcoma through multimodality radiomics integration.

BackgroundA timely assessment of local recurrence (LoR) risk in extremity high-grade osteosarcoma is...

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