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This study proposes an automated system for assessing lung damage severity in coronavirus disease 2019 (COVID-19) patients using computed tomography (CT) images. These preprocessed CT images identify the extent of pulmonary parenchyma (PP) and ground-...

This paper introduces a novel method for transposing summing algorithms, which eliminates the need for an explicit matrix representation of a direct summing operator. Unlike the approach previously proposed in the literature, which relies on ...

Lung diseases cause millions of deaths per year worldwide. For medical diagnosis, different medical images are available, with computed tomography (CT) standing out as effective tools for pathology detection. Recently, the use of artificial ...

The study presented in this paper is devoted to the development of technology for detecting osteoporotic changes in vertebral bodies according to computed tomography data based on the analysis of groups of textural features. This technology will ...

Among CT (Computed Tomography) techniques that produce cross-section images by acquiring X-ray data from multiple angles around the individual, CBCT (Cone Beam CT) that collects the data through cone beam is popular due to its potential to reduce ...

Spleen Epstein-Barr Virus (EBV)-positive inflammatory follicular dendritic cell sarcoma (FDCS) is rare, and the imaging signs are unclear. The COVID-19 has been confirmed to be the cause of pneumonia and can cause a variety of diseases ...

This work demonstrates a hybrid deep learning (DL) model for lung cancer (LC) detection using CT images. Firstly, the input image is passed to the pre-processing stage, where the input image is filtered using a BF and the obtained filtered image is ...

This paper surveys an important class of methods that combine iterative projection methods and variational regularization methods for large-scale inverse problems. Iterative methods such as Krylov subspace methods are invaluable in the numerical linear ...

The study is dedicated to investigating the influence of anatomical peculiarities of the ethmoid sinus and identifying predictors of isolated fungal sphenoiditis development. The introduction highlights the multifactorial nature of the involvement ...

This article describes the principles of creating an intelligent system using a JSM method of automated research support (JSM method ARS) to predict the feasibility of computed tomography application. The procedures of JSM research that are ...

A study has been conducted to determine the feasibility of referring patients with chronic pancreatitis to computed tomography using the JSM method of automated research support. This study structurally repeats a similar study from 2022 but uses ...

The article presents the results of research in the field of computational X-ray tomography, obtained within the framework of the scientific school, by Doctor of Engineering, Corresponding Member of the Russian Academy of Sciences V.L. Arlazarov, ...

In computed tomography and several related scientific domains, the Fourier slice theorem is a powerful mathematical tool to solve the problem of image reconstruction. Although this theorem is well understood in the continuous case, a detailed ...

Mitigating the effects of image appearance due to variations in computed tomography (CT) acquisition and reconstruction parameters is a challenging inverse problem. We present CTFlow, a normalizing flows-based method for harmonizing CT scans ...

The aim of this study was to investigate the robustness of radiomics features extracted from computed tomography (CT) images of patients affected by non-small-cell lung carcinoma (NSCLC). Specifically, the impact of manual segmentation on ...

Coronavirus Disease 2019 (COVID-19) ravaged the world in early 2020, causing great harm to human health. However, there are several challenges to segment the infected areas from computed tomography (CT) image, including blurry boundaries between ...

Simulation-based learning is a crucial educational tool for disciplines involving work-integrated learning and clinical practice. Though its uptake is becoming increasingly common in a range of fields, this uptake is less profound in ...

We introduce CT2Hair, a fully automatic framework for creating high-fidelity 3D hair models that are suitable for use in downstream graphics applications. Our approach utilizes real-world hair wigs as input, and is able to reconstruct hair strands for a ...

Lung nodule detection remains one of the most common and painstaking tasks in radiology. Efforts to aid overworked radiologists are made using artificial intelligence (AI), although computed tomography (CT) makes it a hard computational task in ...

Abdominal wall desmoid-type fibromatoses (AWDF) are occasionally encountered in clinical work, but related CT reports are rare, and most cases were misdiagnosed as malignant tumors.