Radiology

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

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Mask region-based convolutional neural network and VGG-16 inspired brain tumor segmentation.

The process of brain tumour segmentation entails locating the tumour precisely in images. Magnetic R...

Deep Learning-Based Techniques in Glioma Brain Tumor Segmentation Using Multi-Parametric MRI: A Review on Clinical Applications and Future Outlooks.

This comprehensive review explores the role of deep learning (DL) in glioma segmentation using multi...

Artificial intelligence assisted ultrasound for the non-invasive prediction of axillary lymph node metastasis in breast cancer.

PURPOSE: A practical noninvasive method is needed to identify lymph node (LN) status in breast cance...

Deep learning model based on contrast-enhanced ultrasound for predicting vessels encapsulating tumor clusters in hepatocellular carcinoma.

OBJECTIVES: To establish and validate a non-invasive deep learning (DL) model based on contrast-enha...

Deep learning-based automatic ASPECTS calculation can improve diagnosis efficiency in patients with acute ischemic stroke: a multicenter study.

OBJECTIVES: The Alberta Stroke Program Early CT Score (ASPECTS), a systematic method for assessing i...

Differentiation of tuberculous and brucellar spondylitis using conventional MRI-based deep learning algorithms.

PURPOSE: To investigate the feasibility of deep learning (DL) based on conventional MRI to different...

Estimating the Severity of Oral Lesions Via Analysis of Cone Beam Computed Tomography Reports: A Proposed Deep Learning Model.

OBJECTIVES: Several factors such as unavailability of specialists, dental phobia, and financial diff...

AG-MSTLN-EL: A Multi-source Transfer Learning Approach to Brain Tumor Detection.

The analysis of medical images (MI) is an important part of advanced medicine as it helps detect and...

An unrolled neural network for accelerated dynamic MRI based on second-order half-quadratic splitting model.

The reconstruction of dynamic magnetic resonance images from incomplete k-space data has sparked sig...

Ultrasound-based deep learning radiomics nomogram for differentiating mass mastitis from invasive breast cancer.

BACKGROUND: The purpose of this study is to develop and validate the potential value of the deep lea...

Detection of diffusely abnormal white matter in multiple sclerosis on multiparametric brain MRI using semi-supervised deep learning.

In addition to focal lesions, diffusely abnormal white matter (DAWM) is seen on brain MRI of multipl...

Holistic evaluation of a machine learning-based timing calibration for PET detectors under varying data sparsity.

Modern PET scanners offer precise TOF information, improving the SNR of the reconstructed images. Ti...

Deep learning for intracranial aneurysm segmentation using CT angiography.

This study aimed to employ a two-stage deep learning method to accurately detect small aneurysms (4-...

A deep learning-based method for the detection and segmentation of breast masses in ultrasound images.

Automated detection and segmentation of breast masses in ultrasound images are critical for breast c...

Deep learning-based material decomposition of iodine and calcium in mobile photon counting detector CT.

Photon-counting detector (PCD)-based computed tomography (CT) offers several advantages over convent...

Deep learning-based respiratory muscle segmentation as a potential imaging biomarker for respiratory function assessment.

Respiratory diseases significantly affect respiratory function, making them a considerable contribut...

Enabling AI-Generated Content for Gadolinium-Free Contrast-Enhanced Breast Magnetic Resonance Imaging.

BACKGROUND: There is increasing interest in utilizing AI-generated content for gadolinium-free contr...

Transforming Echocardiography: The Role of Artificial Intelligence in Enhancing Diagnostic Accuracy and Accessibility.

Artificial intelligence (AI) has shown transformative potential in various medical fields, including...

Comparison of Explainable Artificial Intelligence Model and Radiologist Review Performances to Detect Breast Cancer in 752 Patients.

OBJECTIVES: Breast cancer is a type of cancer caused by the uncontrolled growth of cells in the brea...

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