AIMC Topic: X-Rays

Clear Filters Showing 381 to 390 of 451 articles

NEURAL NETWORK MODELLING OF CARDIAC DOSE CONVERSION COEFFICIENT FOR ARBITRARY X-RAY SPECTRA.

Radiation protection dosimetry
In this article, an approach to compute the dose conversion coefficients (DCCs) is described for the computational voxel phantom 'High-Definition Reference Korean-Man' (HDRK-Man) using artificial neural networks (ANN). For this purpose, the voxel pha...

Can Gpt-4o Accurately Diagnose Trauma X-Rays? A Comparative Study with Expert Evaluations.

The Journal of emergency medicine
BACKGROUND: The latest artificial intelligence (AI) model, GPT-4o, introduced by OpenAI, can process visual data, presenting a novel opportunity for radiographic evaluation in trauma patients.

YOLO-TARC: YOLOv10 with Token Attention and Residual Convolution for Small Void Detection in Root Canal X-Ray Images.

Sensors (Basel, Switzerland)
The detection of small voids or defects in X-ray images of tooth root canals still faces challenges. To address the issue, this paper proposes an improved YOLOv10 that combines Token Attention with Residual Convolution (ResConv), termed YOLO-TARC. To...

[Development and Application of Deep Learning-Based Model for Quality Control of Children Pelvic X-Ray Images].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
OBJECTIVE: A deep learning-based method for evaluating the quality of pediatric pelvic X-ray images is proposed to construct a diagnostic model and verify its clinical feasibility.

[Deep Learning-Based Key Frame Recognition Algorithm for Adrenal Vascular in X-Ray Imaging].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
Adrenal vein sampling is required for the staging diagnosis of primary aldosteronism, and the frames in which the adrenal veins are presented are called key frames. Currently, the selection of key frames relies on the doctor's visual judgement which ...

Coronary physiology instantaneous wave-free ratio (iFR) derived from x-ray angiography using artificial intelligence deep learning models: a pilot study.

The Journal of invasive cardiology
OBJECTIVES: Coronary angiography (CAG)-derived physiology methods have been developed in an attempt to simplify and increase the usage of coronary physiology, based mostly on dynamic fluid computational algorithms. We aimed to develop a different app...

Multiple semantic X-ray medical image retrieval using efficient feature vector extracted by FPN.

Journal of X-ray science and technology
OBJECTIVE: Content-based medical image retrieval (CBMIR) has become an important part of computer-aided diagnostics (CAD) systems. The complex medical semantic information inherent in medical images is the most difficult part to improve the accuracy ...

A Novel Approach to the Technique of Lung Region Segmentation Based on a Deep Learning Model to Diagnose COVID-19 X-ray Images.

Current medical imaging
BACKGROUND: The novel coronavirus pandemic has caused a global health crisis, placing immense strain on healthcare systems worldwide. Chest X-ray technology has emerged as a critical tool for the diagnosis and treatment of COVID-19. However, the manu...

Multimodality Risk Assessment of Patients with Ischemic Heart Disease Using Deep Learning Models Applied to Electrocardiograms and Chest X-rays.

International heart journal
Comprehensive management approaches for patients with ischemic heart disease (IHD) are important aids for prognostication and treatment planning. While single-modality deep neural networks (DNNs) have shown promising performance for detecting cardiac...

dm-GAN: Distributed multi-latent code inversion enhanced GAN for fast and accurate breast X-ray image automatic generation.

Mathematical biosciences and engineering : MBE
Breast cancer seriously threatens women's physical and mental health. Mammography is one of the most effective methods for breast cancer diagnosis via artificial intelligence algorithms to identify diverse breast masses. The popular intelligent diagn...