Radiology

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

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Showing 1912-1932 of 16,018 articles
Deep Learning techniques to detect and analysis of multiple sclerosis through MRI: A systematic literature review.

Deep learning (DL) techniques represent a rapidly advancing field within artificial intelligence, ga...

Proximity adjusted centroid mapping for accurate detection of nuclei in dense 3D cell systems.

In the past decade, deep learning algorithms have surpassed the performance of many conventional ima...

Artificial intelligence-enhanced magnetic resonance imaging-based pre-operative staging in patients with endometrial cancer.

OBJECTIVE: Evaluation of prognostic factors is crucial in patients with endometrial cancer for optim...

Effect of the Ultrasound-Guided Interscalene and Supraclavicular Blocks on the C4 Dermatome.

PURPOSE: The C4 dermatome anesthesia holds significance for arthroscopic shoulder surgery. However, ...

SMART: Development and Application of a Multimodal Multi-organ Trauma Screening Model for Abdominal Injuries in Emergency Settings.

RATIONALE AND OBJECTIVES: Effective trauma care in emergency departments necessitates rapid diagnosi...

A Fusion Model of MRI Deep Transfer Learning and Radiomics for Discriminating between Pilocytic Astrocytoma and Adamantinomatous Craniopharyngioma.

RATIONALE AND OBJECTIVES: This study aimed to develop and validate a fusion model combining MRI deep...

Noncontrast MRI-based machine learning and radiomics signature can predict the severity of primary lower limb lymphedema.

OBJECTIVE: According to International Lymphology Society guidelines, the severity of lymphedema is d...

Diagnostic performance of neural network algorithms in skull fracture detection on CT scans: a systematic review and meta-analysis.

BACKGROUND AND AIM: The potential intricacy of skull fractures as well as the complexity of underlyi...

Dynamic graph consistency and self-contrast learning for semi-supervised medical image segmentation.

Semi-supervised medical image segmentation endeavors to exploit a limited set of labeled data in con...

Automatic Segmentation of Sylvian Fissure in Brain Ultrasound Images of Pre-Term Infants Using Deep Learning Models.

OBJECTIVE: Segmentation of brain sulci in pre-term infants is crucial for monitoring their developme...

Predicting molecular subtypes of breast cancer based on multi-parametric MRI dataset using deep learning method.

PURPOSE: To develop a multi-parametric MRI model for the prediction of molecular subtypes of breast ...

A quality assessment tool for focused abdominal sonography for trauma examinations using artificial intelligence.

BACKGROUND: Current tools to review focused abdominal sonography for trauma (FAST) images for qualit...

Radiomics and Artificial Intelligence Landscape for [F]FDG PET/CT in Multiple Myeloma.

[F]FDG PET/CT is a powerful imaging modality of high performance in multiple myeloma (MM) and is con...

Deep learning-based prediction of tumor aggressiveness in RCC using multiparametric MRI: a pilot study.

OBJECTIVE: To investigate the value of multiparametric magnetic resonance imaging (MRI) as a non-inv...

Conditional generative diffusion deep learning for accelerated diffusion tensor and kurtosis imaging.

PURPOSE: The purpose of this study was to develop DiffDL, a generative diffusion probabilistic model...

CMFNet: a cross-dimensional modal fusion network for accurate vessel segmentation based on OCTA data.

Optical coherence tomography angiography (OCTA) is a novel non-invasive retinal vessel imaging techn...

A Context-Dependent CNN-Based Framework for Multiple Sclerosis Segmentation in MRI.

Despite several automated strategies for identification/segmentation of Multiple Sclerosis (MS) lesi...

Diagnosis of Fibrotic Interstitial Lung Diseases Based on the Combination of Label-Free Quantitative Multiphoton Fiber Histology and Machine Learning.

Interstitial lung disease (ILD), characterized by inflammation and fibrosis, often suffers from low ...

DCA-Enhanced Alzheimer's detection with shearlet and deep learning integration.

Alzheimer's dementia (AD) is a neurodegenerative disorder that affects the central nervous system, c...

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