Radiology

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

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Deep learning image analysis for continuous single-cell imaging of dynamic processes in Plasmodium falciparum-infected erythrocytes.

Continuous high-resolution imaging of the disease-mediating blood stages of the human malaria parasi...

Multi-center study: ultrasound-based deep learning features for predicting Ki-67 expression in breast cancer.

Applying deep learning algorithms to mine ultrasound features of breast cancer and construct a machi...

Machine learning based radiomics approach for outcome prediction of meningioma - a systematic review.

INTRODUCTION: Meningioma is the most common brain tumor in adults. Magnetic resonance imaging (MRI) ...

Optimizing imaging modalities for sarcoma subtypes in radiation therapy: State of the art.

The choice of imaging modalities is essential in sarcoma management, as different techniques provide...

A new era in nephrology: the role of super-resolution microscopy in research, medical diagnostic, and drug discovery.

For decades, electron microscopy has been the primary method to visualize ultrastructural details of...

Proof-of-Concept Prompted Large Language Model for Radiology Procedure Request Routing.

PURPOSE: To measure the accuracy and cost of a proof-of-concept prompted large language model to rou...

Brain tumor intelligent diagnosis based on Auto-Encoder and U-Net feature extraction.

Preoperative classification of brain tumors is critical to developing personalized treatment plans, ...

Physics Informed Neural Networks for Electrical Impedance Tomography.

Electrical Impedance Tomography (EIT) is an imaging modality used to reconstruct the internal conduc...

Integrating data mining with transcranial focused ultrasound to refine neuralgia treatment strategies.

BACKGROUND: Neuralgia and other neuropathic pain are difficult to treat owing to their complicated e...

Development and validation of pan-cancer lesion segmentation AI-model for whole-body 18F-FDG PET/CT in diverse clinical cohorts.

BACKGROUND: This study develops a deep learning-based automated lesion segmentation model for whole-...

SpineMamba: Enhancing 3D spinal segmentation in clinical imaging through residual visual Mamba layers and shape priors.

Accurate segmentation of three-dimensional (3D) clinical medical images is critical for the diagnosi...

Artificial intelligence-assisted magnetic resonance lymphography for evaluation of micro- and macro-sentinel lymph node metastasis in breast cancer.

Contrast-enhanced magnetic resonance lymphography (CE-MRL) plays a crucial role in preoperative diag...

Infection and Inflammation in Nuclear Medicine Imaging: The Role of Artificial Intelligence.

Infectious and inflammatory diseases represent a global challenge. Delayed diagnosis and treatment l...

Deep learning informed multimodal fusion of radiology and pathology to predict outcomes in HPV-associated oropharyngeal squamous cell carcinoma.

BACKGROUND: We aim to predict outcomes of human papillomavirus (HPV)-associated oropharyngeal squamo...

Machine learning-based radiomics using MRI to differentiate early-stage Duchenne and Becker muscular dystrophy in children.

OBJECTIVES: Duchenne muscular dystrophy (DMD) and Becker muscular dystrophy (BMD) present similar sy...

High-resolution ultrasound of the annular pulley system in the toes: sonographic anatomy and pathological cases.

OBJECTIVE: To validate high-frequency ultrasound as a valuable imaging modality in the assessment of...

Deep Guess acceleration for explainable image reconstruction in sparse-view CT.

Sparse-view Computed Tomography (CT) is an emerging protocol designed to reduce X-ray dose radiation...

Deformable image registration with strategic integration pyramid framework for brain MRI.

Medical image registration plays a crucial role in medical imaging, with a wide range of clinical ap...

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