Radiology

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

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Prompt2Perturb (P2P): Text-Guided Diffusion-Based Adversarial Attacks on Breast Ultrasound Images

Deep neural networks (DNNs) offer significant promise for improving breast cancer diagnosis in med...

Structurally Consistent MRI Colorization using Cross-modal Fusion Learning

Medical image colorization can greatly enhance the interpretability of the underlying imaging moda...

Embeddings are all you need! Achieving High Performance Medical Image Classification through Training-Free Embedding Analysis

Developing artificial intelligence (AI) and machine learning (ML) models for medical imaging typic...

Multi-Stage Segmentation and Cascade Classification Methods for Improving Cardiac MRI Analysis

The segmentation and classification of cardiac magnetic resonance imaging are critical for diagnos...

MaskTerial: A Foundation Model for Automated 2D Material Flake Detection

The detection and classification of exfoliated two-dimensional (2D) material flakes from optical m...

Radiology Report Generation via Multi-objective Preference Optimization

Automatic Radiology Report Generation (RRG) is an important topic for alleviating the substantial ...

Novel 3D Binary Indexed Tree for Volume Computation of 3D Reconstructed Models from Volumetric Data

In the burgeoning field of medical imaging, precise computation of 3D volume holds a significant i...

ConDSeg: A General Medical Image Segmentation Framework via Contrast-Driven Feature Enhancement

Medical image segmentation plays an important role in clinical decision making, treatment planning...

A semi-supervised deep neuro-fuzzy iterative learning system for automatic segmentation of hippocampus brain MRI.

The hippocampus is a small, yet intricate seahorse-shaped tiny structure located deep within the bra...

Dec 2024 39807055
SKIPNet: Spatial Attention Skip Connections for Enhanced Brain Tumor Classification

Early detection of brain tumors through magnetic resonance imaging (MRI) is essential for timely t...

Motion Artifact Removal in Pixel-Frequency Domain via Alternate Masks and Diffusion Model

Motion artifacts present in magnetic resonance imaging (MRI) can seriously interfere with clinical...

Enhanced MRI Representation via Cross-series Masking

Magnetic resonance imaging (MRI) is indispensable for diagnosing and planning treatment in various...

Label up: Learning Pulmonary Embolism Segmentation from Image Level Annotation through Model Explainability

Pulmonary Embolisms (PE) are a leading cause of cardiovascular death. Computed tomographic pulmona...

Quantitative Comparison of the Total Focusing Method, Reverse Time Migration, and Full Waveform Inversion for Ultrasonic Imaging

Phased array ultrasound is a widely used technique in non-destructive testing. Using piezoelectric...

QCResUNet: Joint Subject-level and Voxel-level Segmentation Quality Prediction

Deep learning has made significant strides in automated brain tumor segmentation from magnetic res...

Hyperbolic embedding of brain networks can predict the surgery outcome in temporal lobe epilepsy

Epilepsy surgery, particularly for temporal lobe epilepsy (TLE), remains a vital treatment option ...

Toward Non-Invasive Diagnosis of Bankart Lesions with Deep Learning

Bankart lesions, or anterior-inferior glenoid labral tears, are diagnostically challenging on stan...

FedSynthCT-Brain: A Federated Learning Framework for Multi-Institutional Brain MRI-to-CT Synthesis

The generation of Synthetic Computed Tomography (sCT) images has become a pivotal methodology in m...

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