Radiology

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

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Evaluation of the prostate cancer and its metastases in the [ 68 Ga]Ga-PSMA PET/CT images: deep learning method vs. conventional PET/CT processing.

PURPOSE: This study demonstrates the feasibility and benefits of using a deep learning-based approac...

A Scoping Review of Machine-Learning Derived Radiomic Analysis of CT and PET Imaging to Investigate Atherosclerotic Cardiovascular Disease.

BACKGROUND: Cardiovascular disease affects the carotid arteries, coronary arteries, aorta and the pe...

Advancing Tau PET Quantification in Alzheimer Disease with Machine Learning: Introducing THETA, a Novel Tau Summary Measure.

Alzheimer disease (AD) exhibits spatially heterogeneous 3- or 4-repeat tau deposition across partici...

Magnetic Resonance Electrical Properties Tomography Based on Modified Physics- Informed Neural Network and Multiconstraints.

This paper presents a novel method based on leveraging physics-informed neural networks for magnetic...

Cost-Sensitive Weighted Contrastive Learning Based on Graph Convolutional Networks for Imbalanced Alzheimer's Disease Staging.

Identifying the progression stages of Alzheimer's disease (AD) can be considered as an imbalanced mu...

Deep Location Soft-Embedding-Based Network With Regional Scoring for Mammogram Classification.

Early detection and treatment of breast cancer can significantly reduce patient mortality, and mammo...

Machine learning-assisted diagnosis of parotid tumor by using contrast-enhanced CT imaging features.

PURPOSE: This study aims to develop a machine learning diagnostic model for parotid gland tumors bas...

Super-Resolving and Denoising 4D flow MRI of Neurofluids Using Physics-Guided Neural Networks.

PURPOSE: To obtain high-resolution velocity fields of cerebrospinal fluid (CSF) and cerebral blood f...

Mammography classification with multi-view deep learning techniques: Investigating graph and transformer-based architectures.

The potential and promise of deep learning systems to provide an independent assessment and relieve ...

Automated MRI-based segmentation of intracranial arterial calcification by restricting feature complexity.

PURPOSE: To develop an automated deep learning model for MRI-based segmentation and detection of int...

High-quality expert annotations enhance artificial intelligence model accuracy for osteosarcoma X-ray diagnosis.

Primary malignant bone tumors, such as osteosarcoma, significantly affect the pediatric and young ad...

Assessment of multi-modal magnetic resonance imaging for glioma based on a deep learning reconstruction approach with the denoising method.

BACKGROUND: Deep learning reconstruction (DLR) with denoising has been reported as potentially impro...

Magnetic Resonance-Guided Cancer Therapy Radiomics and Machine Learning Models for Response Prediction.

Magnetic resonance imaging (MRI) is known for its accurate soft tissue delineation of tumors and nor...

Impact of acquisition area on deep-learning-based glaucoma detection in different plexuses in OCTA.

Glaucoma is a group of neurodegenerative diseases that can lead to irreversible blindness. Yet, the ...

Learning co-plane attention across MRI sequences for diagnosing twelve types of knee abnormalities.

Multi-sequence magnetic resonance imaging is crucial in accurately identifying knee abnormalities bu...

Preoperative prediction model of lymph node metastasis in the inguinal and femoral region based on radiomics and artificial intelligence.

OBJECTIVE: To predict preoperative inguinal lymph node metastasis in vulvar cancer patients using a ...

Automated classification of mandibular canal in relation to third molar using CBCT images.

BACKGROUND: Dental radiology has significantly benefited from cone-beam computed tomography (CBCT) b...

Artificial intelligence-based extraction of quantitative ultra-widefield fluorescein angiography parameters in retinal vein occlusion.

OBJECTIVE: To examine the association between quantitative vascular parameters extracted from intrav...

Deep unfolding network with spatial alignment for multi-modal MRI reconstruction.

Multi-modal Magnetic Resonance Imaging (MRI) offers complementary diagnostic information, but some m...

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