Radiology

PET/CT-based deep learning grading signature to optimize surgical decisions for clinical stage I invasive lung adenocarcinoma and biologic basis under its prediction: a multicenter study.

PURPOSE: No consensus on a grading system for invasive lung adenocarcinoma had been built over a lon...

Selecting cardiac magnetic resonance images suitable for annotation of pulmonary arteries using an active-learning based deep learning model.

An increasing and aging patient population poses a growing burden on healthcare professionals. Autom...

Predicting carcass tissue composition in Blackbelly sheep using ultrasound measurements and machine learning methods.

This study aimed to predict Blackbelly sheep carcass tissue composition using ultrasound measurement...

Deep Learning-Based Model for Automatic Assessment of Anterior Angle Chamber in Ultrasound Biomicroscopy.

OBJECTIVE: The goal of the work described here was to develop and assess a deep learning-based model...

Three-dimensional CT imaging in extensor tendons using deep learning reconstruction: optimal reconstruction parameters and the influence of dose.

The purpose of this study was to assess the optimal reconstruction parameters and the influence of t...

Research on texture images and radiomics in urology: a review of urological MR imaging applications.

PURPOSE OF REVIEW: Tumor volume and heterogenicity are associated with diagnosis and prognosis of ur...

Region of interest focused MRI to synthetic CT translation using regression and segmentation multi-task network.

. In MR-only clinical workflow, replacing CT with MR image is of advantage for workflow efficiency a...

A deep sift convolutional neural networks for total brain volume estimation from 3D ultrasound images.

Preterm infants are a highly vulnerable population. The total brain volume (TBV) of these infants ca...

Automated Segmentation of Optical Coherence Tomography Images of the Human Tympanic Membrane Using Deep Learning.

Optical Coherence Tomography (OCT) is a light-based imaging modality that is used widely in the diag...

Computational Cardiology: The Door to the Future of Interventional Cardiology.

Deep learning in MRI-guided radiation therapy: A systematic review.

Recent advances in MRI-guided radiation therapy (MRgRT) and deep learning techniques encourage fully...

Using deep learning models in magnetic resonance cholangiopancreatography images to diagnose common bile duct stones.

BACKGROUNDS AND AIMS: Magnetic resonance cholangiopancreatography (MRCP) plays a significant role in...

Gray-to-color image conversion in the classification of breast lesions on ultrasound using pre-trained deep neural networks.

Breast ultrasound (BUS) image classification in benign and malignant classes is often based on pre-t...

Deep learning based source imaging provides strong sublobar localization of epileptogenic zone from MEG interictal spikes.

Electromagnetic source imaging (ESI) offers unique capability of imaging brain dynamics for studying...

As artificial intelligence goes multimodal, medical applications multiply.

Machines don't have eyes, but you wouldn't know that if you followed the progression of deep learnin...

AI-integrated ocular imaging for predicting cardiovascular disease: advancements and future outlook.

Cardiovascular disease (CVD) remains the leading cause of death worldwide. Assessing of CVD risk pla...

Assessing AI-Powered Patient Education: A Case Study in Radiology.

RATIONALE AND OBJECTIVES: With recent advancements in the power and accessibility of artificial inte...

Deep learning-based iodine contrast-augmenting algorithm for low-contrast-dose liver CT to assess hypovascular hepatic metastasis.

PURPOSE: To investigate the image quality and diagnostic performance of low-contrast-dose liver CT u...

Multicentric Ga-PSMA PET radiomics for treatment response assessment of Lu-PSMA-617 radioligand therapy in patients with metastatic castration-resistant prostate cancer.

OBJECTIVE: The treatment with Lutetium PSMA (Lu-PSMA) in patients with metastatic castration-resista...

Prediction of pathological complete response to neoadjuvant chemotherapy in locally advanced breast cancer by using a deep learning model with 18F-FDG PET/CT.

OBJECTIVES: The aim of the study is 18F-FDG PET/CT imaging by using deep learning method are predict...

Evaluation of a Deep Learning-based Algorithm for Post-Radiotherapy Prostate Cancer Local Recurrence Detection Using Biparametric MRI.

OBJECTIVE: To evaluate a biparametric MRI (bpMRI)-based artificial intelligence (AI) model for the d...