Related papers: A Deep Ensemble Learning Approach to Lung CT Segme…

Chest X-rays of coronavirus disease 2019 (COVID-19) patients are frequently obtained to determine the extent of lung disease and are a valuable source of data for creating artificial intelligence models. Most work to date assessing disease…

A novel coronavirus disease 2019 (COVID-19) was detected and has spread rapidly across various countries around the world since the end of the year 2019, Computed Tomography (CT) images have been used as a crucial alternative to the…

The COVID-19 pandemic has inspired unprecedented data collection and computer vision modelling efforts worldwide, focusing on diagnosis and stratification of COVID-19 from medical images. Despite this large-scale research effort, these…

The current COVID-19 pandemic overloads healthcare systems, including radiology departments. Though several deep learning approaches were developed to assist in CT analysis, nobody considered study triage directly as a computer science…

Automated segmentation of lung abnormalities in computed tomography is an important step for diagnosing and characterizing lung disease. In this work, we improve upon a previous method and propose S-MEDSeg, a deep learning based approach…

Due to the irregular shapes,various sizes and indistinguishable boundaries between the normal and infected tissues, it is still a challenging task to accurately segment the infected lesions of COVID-19 on CT images. In this paper, a novel…

Background: The 2019 novel coronavirus disease (COVID-19) has been spread widely in the world, causing a huge threat to people's living environment. Objective: Under computed tomography (CT) imaging, the structure features of COVID-19…

During the COVID-19 pandemic, medical imaging techniques like computed tomography (CT) scans have demonstrated effectiveness in combating the rapid spread of the virus. Therefore, it is crucial to conduct research on computerized models for…

Since 2019, the global dissemination of the Coronavirus and its novel strains has resulted in a surge of new infections. The use of X-ray and computed tomography (CT) imaging techniques is critical in diagnosing and managing COVID-19.…

Objectives: To investigate machine-learning classifiers and interpretable models using chest CT for detection of COVID-19 and differentiation from other pneumonias, ILD and normal CTs. Methods: Our retrospective multi-institutional study…

To counter the outbreak of COVID-19, the accurate diagnosis of suspected cases plays a crucial role in timely quarantine, medical treatment, and preventing the spread of the pandemic. Considering the limited training cases and resources…

Since COVID strongly affects the respiratory system, lung CT-scans can be used for the analysis of a patients health. We introduce a neural network for the prediction of the severity of lung damage and the detection of a COVID-infection…

The novelty of the COVID-19 disease and the speed of spread has created a colossal chaos, impulse among researchers worldwide to exploit all the resources and capabilities to understand and analyze characteristics of the coronavirus in term…

Since the emergence of Covid-19 in late 2019, medical image analysis using artificial intelligence (AI) has emerged as a crucial research area, particularly with the utility of CT-scan imaging for disease diagnosis. This paper contributes…

The COVID-19 pandemic presented numerous challenges to healthcare systems worldwide. Given that lung infections are prevalent among COVID-19 patients, chest Computer Tomography (CT) scans have frequently been utilized as an alternative…

Improving automated analysis of medical imaging will provide clinicians more options in providing care for patients. The 2023 AI-enabled Medical Image Analysis Workshop and Covid-19 Diagnosis Competition (AI-MIA-COV19D) provides an…

Automated lobar segmentation allows regional evaluation of lung disease and is important for diagnosis and therapy planning. Advanced statistical workflows permitting such evaluation is a needed area within respiratory medicine; their…

This study aimed to evaluate the performance of a novel unsupervised deep learning-based framework for automated infections lesion segmentation from CT images of Covid patients. In the first step, two residual networks were independently…

COVID-19 is a severe and acute viral disease that can cause symptoms consistent with pneumonia in which inflammation is caused in the alveolous regions of the lungs leading to a build-up of fluid and breathing difficulties. Thus, the…

Chest X-rays have been widely used for COVID-19 screening; however, 3D computed tomography (CT) is a more effective modality. We present our findings on COVID-19 severity prediction from chest CT scans using the STOIC dataset. We developed…