Radiology

A Joint Group Sparsity-based deep learning for multi-contrast MRI reconstruction.

Multi-contrast magnetic resonance imaging (MRI) can provide richer diagnosis information. The data a...

Telerobotic Sonography for Remote Diagnostic Imaging.

Deep learning-based noise reduction for coronary CT angiography: using four-dimensional noise-reduction images as the ground truth.

BACKGROUND: To assess low-contrast areas such as plaque and coronary artery stenosis, coronary compu...

Fully automated cardiac MRI segmentation using dilated residual network.

PURPOSE: Cardiac ventricle segmentation from cine magnetic resonance imaging (CMRI) is a recognized ...

Convolutional neural network -based phantom image scoring for mammography quality control.

BACKGROUND: Visual evaluation of phantom images is an important, but time-consuming part of mammogra...

Capsule robot pose and mechanism state detection in ultrasound using attention-based hierarchical deep learning.

Ingestible robotic capsules with locomotion capabilities and on-board sampling mechanism have great ...

A Deep Learning Model for Automatic Detection and Classification of Disc Herniation in Magnetic Resonance Images.

Localization of lumbar discs in magnetic resonance imaging (MRI) is a challenging task, due to a vas...

Feasibility of a lung airway navigation system using fiber-Bragg shape sensing and artificial intelligence for early diagnosis of lung cancer.

Currently early diagnosis of malignant lesions at the periphery of lung parenchyma requires guidance...

Diffusion-weighted MRI with deep learning for visualizing treatment results of MR-guided HIFU ablation of uterine fibroids.

OBJECTIVES: No method is available to determine the non-perfused volume (NPV) repeatedly during magn...

Predicting Hypoperfusion Lesion and Target Mismatch in Stroke from Diffusion-weighted MRI Using Deep Learning.

Background Perfusion imaging is important to identify a target mismatch in stroke but requires contr...

Artificial intelligence in diagnostic and interventional radiology: Where are we now?

The emergence of massively parallel yet affordable computing devices has been a game changer for res...

Dual segmentation models for poorly and well-differentiated hepatocellular carcinoma using two-step transfer deep learning on dynamic contrast-enhanced CT images.

The aim of this study was to develop dual segmentation models for poorly and well-differentiated hep...

Deep neural network automated segmentation of cellular structures in volume electron microscopy.

Volume electron microscopy is an important imaging modality in contemporary cell biology. Identifica...

Artificial intelligence in veterinary diagnostic imaging: A literature review.

Artificial intelligence in veterinary medicine is an emerging field. Machine learning, a subfield of...

Deep learning-based motion compensation for four-dimensional cone-beam computed tomography (4D-CBCT) reconstruction.

BACKGROUND: Motion-compensated (MoCo) reconstruction shows great promise in improving four-dimension...

Ultrasound Probe and Hand-Eye Calibrations for Robot-Assisted Needle Biopsy.

In robot-assisted ultrasound-guided needle biopsy, it is essential to conduct calibration of the ult...

Introduction.

Endoscopic ultrasound (EUS) was born from the combination of a high-frequency ultrasound probe with ...

Application of deblur technology for improving the clarity of digital subtractive angiography.

BACKGROUND: Digital subtraction angiography (DSA) is most commonly used in vessel disease examinatio...

Artificial intelligence for localization of the acute ischemic stroke by non-contrast computed tomography.

A non-contrast cranial computer tomography (ncCT) is often employed for the diagnosis of the early s...

Efficient framework for brain tumor detection using different deep learning techniques.

The brain tumor is an urgent malignancy caused by unregulated cell division. Tumors are classified u...

A CT-Based Deep Learning Radiomics Nomogram to Predict Histological Grades of Head and Neck Squamous Cell Carcinoma.

RATIONALE AND OBJECTIVES: Accurate pretreatment assessment of histological differentiation grade of ...