Radiology

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

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Self-supervised learning for MRI reconstruction through mapping resampled k-space data to resampled k-space data.

In recent years, significant advancements have been achieved in applying deep learning (DL) to magne...

Thorax-encompassing multi-modality PET/CT deep learning model for resected lung cancer prognostication: A retrospective, multicenter study.

BACKGROUND: Patients with early-stage non-small cell lung cancer (NSCLC) typically receive surgery a...

Radiomic study of common sellar region lesions differentiation in magnetic resonance imaging based on multi-classification machine learning model.

OBJECTIVE: Pituitary adenomas (PAs), craniopharyngiomas (CRs), Rathke's cleft cysts (RCCs), and tube...

Multimodal GPT model for assisting thyroid nodule diagnosis and management.

Although using artificial intelligence (AI) to analyze ultrasound images is a promising approach to ...

Surgical and radiological outcomes of giant cell tumor of the bone: prognostic value of Campanacci grading and selective use of denosumab.

BACKGROUND: Advancements in diagnostic and therapeutic modalities for giant cell tumors of bone (GCT...

Prediction of anthropogenic I in the South China Sea based on machine learning.

With the rapid increase in the number of nuclear power plants along the China coast and the potentia...

A systematic review on deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction.

BACKGROUND: Coronary artery disease (CAD) is a major worldwide health concern, contributing signific...

Deep learning-based acceleration of high-resolution compressed sense MR imaging of the hip.

PURPOSE: To evaluate a Compressed Sense Artificial Intelligence framework (CSAI) incorporating paral...

Automatic ultrasound image alignment for diagnosis of pediatric distal forearm fractures.

PURPOSE: The study aims to develop an automatic method to align ultrasound images of the distal fore...

Deep Learning-Based Algorithm for Automatic Quantification of Nigrosome-1 and Parkinsonism Classification Using Susceptibility Map-Weighted MRI.

BACKGROUND AND PURPOSE: The diagnostic performance of deep learning model that simultaneously detect...

Development and Evaluation of Automated Artificial Intelligence-Based Brain Tumor Response Assessment in Patients with Glioblastoma.

This project aimed to develop and evaluate an automated, AI-based, volumetric brain tumor MRI respon...

Deep learning model for predicting the RAS oncogene status in colorectal cancer liver metastases.

BACKGROUND: To develop a deep learning radiomics (DLR) model based on contrast-enhanced computed tom...

Model-Based Convolution Neural Network for 3D Near-Infrared Spectral Tomography.

Near-infrared spectral tomography (NIRST) is a non-invasive imaging technique that provides function...

High-Resolution Maps of Left Atrial Displacements and Strains Estimated With 3D Cine MRI Using Online Learning Neural Networks.

The functional analysis of the left atrium (LA) is important for evaluating cardiac health and under...

Spatiotemporal Implicit Neural Representation for Unsupervised Dynamic MRI Reconstruction.

Supervised Deep-Learning (DL)-based reconstruction algorithms have shown state-of-the-art results fo...

Electrode Arrays for Detecting and Modulating Deep Brain Neural Information in Primates: A Review.

Primates possess a more developed central nervous system and a higher level of intelligence than rod...

A deep learning algorithm for automated adrenal gland segmentation on non-contrast CT images.

BACKGROUND: The adrenal glands are small retroperitoneal organs, few reference standards exist for a...

Artifact estimation network for MR images: effectiveness of batch normalization and dropout layers.

BACKGROUND: Magnetic resonance imaging (MRI) is an essential tool for medical diagnosis. However, ar...

Characterization of Effective Half-Life for Instant Single-Time-Point Dosimetry Using Machine Learning.

Single-time-point (STP) image-based dosimetry offers a more convenient approach for clinical practic...

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