Radiology

An rs-fMRI based neuroimaging marker for adult absence epilepsy.

OBJECTIVE: Approximately 20-30 % of epilepsy patients exhibit negative findings on routine magnetic ...

Artificial Intelligence and Multiple Sclerosis.

In this paper, we analyse the different advances in artificial intelligence (AI) approaches in multi...

Prostate cancer diagnosis based on multi-parametric MRI, clinical and pathological factors using deep learning.

Prostate cancer is one of the most common and fatal diseases among men, and its early diagnosis can ...

ISLE: An Intelligent Streaming Framework for High-Throughput AI Inference in Medical Imaging.

As the adoption of artificial intelligence (AI) systems in radiology grows, the increase in demand f...

Radiologists' perceptions on AI integration: An in-depth survey study.

PURPOSE: To assess the perceptions and attitudes of radiologists toward the adoption of artificial i...

Radiomics and artificial intelligence applications in pediatric brain tumors.

BACKGROUND: The study of central nervous system (CNS) tumors is particularly relevant in the pediatr...

Applications of artificial intelligence in diagnosis of uncommon cystoid macular edema using optical coherence tomography imaging: A systematic review.

Cystoid macular edema (CME) is a sight-threatening condition often associated with inflammatory and ...

Artificial Intelligence for Otosclerosis Detection: A Pilot Study.

The gold standard for otosclerosis diagnosis, aside from surgery, is high-resolution temporal bone c...

Deep Learning for Describing Breast Ultrasound Images with BI-RADS Terms.

Breast cancer is the most common cancer in women. Ultrasound is one of the most used techniques for ...

Predicting changes in brain metabolism and progression from mild cognitive impairment to dementia using multitask Deep Learning models and explainable AI.

BACKGROUND: The prediction of Alzheimer's disease (AD) progression from its early stages is a resear...

Reshaping free-text radiology notes into structured reports with generative question answering transformers.

BACKGROUND: Radiology reports are typically written in a free-text format, making clinical informati...

Artificial intelligence for neuro MRI acquisition: a review.

OBJECT: To review recent advances of artificial intelligence (AI) in enhancing the efficiency and th...

Identifying significant structural factors associated with knee pain severity in patients with osteoarthritis using machine learning.

Our main objective was to use machine learning methods to identify significant structural factors as...

Fluorescence excitation-scanning hyperspectral imaging with scalable 2D-3D deep learning framework for colorectal cancer detection.

Colorectal cancer is one of the top contributors to cancer-related deaths in the United States, with...

Artificial intelligence and personalized diagnostics in periodontology: A narrative review.

Periodontal diseases pose a significant global health burden, requiring early detection and personal...

Comparison of image quality between Deep learning image reconstruction and Iterative reconstruction technique for CT Brain- a pilot study.

BACKGROUND: Non-contrast Computed Tomography (NCCT) plays a pivotal role in assessing central nervou...

Motion robust coronary MR angiography using zigzag centric ky-kz trajectory and high-resolution deep learning reconstruction.

PURPOSE: To develop a new MR coronary angiography (MRCA) technique by employing a zigzag fan-shaped ...

Suppressing the HIFU interference in ultrasound guiding images with a diffusion-based deep learning model.

BACKGROUND AND OBJECTIVES: In ultrasound guided high-intensity focused ultrasound (HIFU) surgery, it...

Artificial Intelligence Based Methods to Enhance Analysis of Non-Contrast Computed Tomography in Patients with Aortic Aneurysm.

Immune Cell-Based Microrobots for Remote Magnetic Actuation, Antitumor Activity, and Medical Imaging.

Translating medical microrobots into clinics requires tracking, localization, and performing assigne...

CMRxRecon: A publicly available k-space dataset and benchmark to advance deep learning for cardiac MRI.

Cardiac magnetic resonance imaging (CMR) has emerged as a valuable diagnostic tool for cardiac disea...