Radiology

Sensitivity of a deep-learning-based breast cancer risk prediction model.

When it comes to the implementation of deep-learning based breast cancer risk (BCR) prediction model...

Feasibility of U-Net model for cerebral arteries segmentation with low-dose computed tomography angiographic images with pre-processing methods.

Subtraction computed tomography angiography (sCTA) can effectively separate enhanced cerebral arteri...

Deep Learning-Driven Abbreviated Shoulder MRI Protocols: Diagnostic Accuracy in Clinical Practice.

BACKGROUND: Deep learning (DL) reconstruction techniques have shown promise in reducing MRI acquisit...

An Ultrasound-based Machine Learning Model for Predicting Tumor-Infiltrating Lymphocytes in Breast Cancer.

IntroductionTumor-infiltrating lymphocytes (TILs) are key indicators of immune response and prognosi...

Enhancing Specificity in Predicting Axillary Lymph Node Metastasis in Breast Cancer through an Interpretable Machine Learning Model with CEM and Ultrasound Integration.

IntroductionThe study aims to evaluate the performance of an interpretable machine learning model in...

Quantitative Ischemic Lesions of Portable Low-Field Strength MRI Using Deep Learning-Based Super-Resolution.

BACKGROUND: Deep learning-based synthetic super-resolution magnetic resonance imaging (SynthMRI) may...

Deep learning-based automatic segmentation of cerebral infarcts on diffusion MRI.

We explored effects of (1) training with various sample sizes of multi-site vs. single-site training...

A multimodal MRI-based machine learning framework for classifying cognitive impairment in cerebral small vessel disease.

The heterogeneity of cerebral small vessel disease (CSVD) with mild cognitive impairment (MCI) prese...

AI-assisted SERS imaging method for label-free and rapid discrimination of clinical lymphoma.

BACKGROUND: Lymphoma is a malignant tumor of the immune system and its incidence is increasing year ...

Multimodal Large Language Model With Knowledge Retrieval Using Flowchart Embedding for Forming Follow-Up Recommendations for Pancreatic Cystic Lesions.

The American College of Radiology (ACR) Incidental Findings Committee (IFC) algorithm provides guid...

Artificial Intelligence in CT Angiography for the Detection of Coronary Artery Stenosis and Calcified Plaque: A Systematic Review and Meta-analysis.

PURPOSE: We aimed to evaluate the diagnostic performance of artificial intelligence (AI) in detectin...

Sonopermeation combined with stroma normalization enables complete cure using nano-immunotherapy in murine breast tumors.

Nano-immunotherapy shows great promise in improving patient outcomes, as seen in advanced triple-neg...

Chronic Total Occlusion Percutaneous Coronary Intervention: Present and Future.

Chronic total occlusion percutaneous coronary intervention has evolved into a subspecialty of interv...

Ultrasound-activated piezoelectric biomaterials for cartilage regeneration.

Due to the low density of chondrocytes and limited ability to repair damaged extracellular matrix (E...

Utilizing Pix2Pix conditional generative adversarial networks to recover missing data in preclinical PET scanner sinogram gaps.

BACKGROUND: The presence of a gap between adjacent detector blocks in Positron Emission Tomography (...

A dual-branch hybrid network with bilateral-difference awareness for collateral scoring on CT angiography of acute ischemic stroke patients.

Acute ischemic stroke (AIS) patients with good collaterals tend to have better outcomes after endova...

Depth-of-interaction encoding techniques for pixelated PET detectors enabled by machine learning methods and fast waveform digitization.

. Pixelated detectors with single-ended readout are routinely used by commercial positron emission t...

A radiomics approach to distinguish Progressive Supranuclear Palsy Richardson's syndrome from other phenotypes starting from MR images.

BACKGROUND AND OBJECTIVE: Progressive Supranuclear Palsy (PSP) is an uncommon neurodegenerative diso...

HALSR-Net: Improving CNN Segmentation of Cardiac Left Ventricle MRI with Hybrid Attention and Latent Space Reconstruction.

Accurate cardiac MRI segmentation is vital for detailed cardiac analysis, yet the manual process is ...

Comment on "IR-GPT: AI Foundation Models to Optimize Interventional Radiology".

Future prospects of deep learning in esophageal cancer diagnosis and clinical decision support (Review).

Esophageal cancer (EC) is one of the leading causes of cancer-related mortality worldwide, still fac...