AI Medical Compendium Journal:
Journal of X-ray science and technology

Showing 51 to 60 of 116 articles

Deep learning classifiers for computer-aided diagnosis of multiple lungs disease.

Journal of X-ray science and technology
BACKGROUND: Computer aided diagnosis has gained momentum in the recent past. The advances in deep learning and availability of huge volumes of data along with increased computational capabilities has reshaped the diagnosis and prognosis procedures.

Performance of deep learning in classifying malignant primary and metastatic brain tumors using different MRI sequences: A medical analysis study.

Journal of X-ray science and technology
BACKGROUND: Malignant Primary Brain Tumor (MPBT) and Metastatic Brain Tumor (MBT) are the most common types of brain tumors, which require different management approaches. Magnetic Resonance Imaging (MRI) is the most frequently used modality for asse...

Dual-domain fusion deep convolutional neural network for low-dose CT denoising.

Journal of X-ray science and technology
BACKGROUND: In view of the underlying health risks posed by X-ray radiation, the main goal of the present research is to achieve high-quality CT images at the same time as reducing x-ray radiation. In recent years, convolutional neural network (CNN) ...

Deep convolutional neural network based hyperspectral brain tissue classification.

Journal of X-ray science and technology
BACKGROUND: Hyperspectral brain tissue imaging has been recently utilized in medical research aiming to study brain science and obtain various biological phenomena of the different tissue types. However, processing high-dimensional data of hyperspect...

Deep learning image reconstruction for quality assessment of iodine concentration in computed tomography: A phantom study.

Journal of X-ray science and technology
BACKGROUND: Recently, deep learning reconstruction (DLR) technology aiming to improve image quality with minimal radiation dose has been applied not only to pediatric scans, but also to computed tomography angiography (CTA).

A deep learning-based recognition for dangerous objects imaged in X-ray security inspection device.

Journal of X-ray science and technology
Several limitations in algorithms and datasets in the field of X-ray security inspection result in the low accuracy of X-ray image inspection. In the literature, there have been rare studies proposed and datasets prepared for the topic of dangerous o...

Low-dose CT noise reduction based on local total variation and improved wavelet residual CNN.

Journal of X-ray science and technology
BACKGROUND: Low-dose computed tomography (LDCT) is an effective method for reducing radiation exposure. However, reducing radiation dose leads to considerable noise in the reconstructed image that can affect doctor's judgment.

Estimation of patient's angle from skull radiographs using deep learning.

Journal of X-ray science and technology
BACKGROUND: Skull radiography, an assessment method for initial diagnosis and post-operative follow-up, requires substantial retaking of various types of radiographs. During retaking, a radiologic technologist estimates a patient's rotation angle fro...

An interpretable multi-task system for clinically applicable COVID-19 diagnosis using CXR.

Journal of X-ray science and technology
BACKGROUND: With the emergence of continuously mutating variants of coronavirus, it is urgent to develop a deep learning model for automatic COVID-19 diagnosis at early stages from chest X-ray images. Since laboratory testing is time-consuming and re...

Spark plug defects detection based on improved Faster-RCNN algorithm.

Journal of X-ray science and technology
The objective of this study is to apply an improved Faster-RCNN model in order to solve the problems of low detection accuracy and slow detection speed in spark plug defect detection. In detail, an attention module based symmetrical convolutional net...