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With a Coronavirus disease (COVID-19) case count exceeding 10 million worldwide, there is an increased need for a diagnostic capability. The main variables in increasing diagnostic capability are reduced cost, turnaround or diagnosis time,…

图像与视频处理 · 电气工程与系统科学 2020-09-21 Hussin K. Ragb , Ian T. Dover , Redha Ali

The advent of 2019 Coronavirus (COVID-19) has engendered a momentous global health crisis, necessitating the identification of the ailment in individuals through diverse diagnostic modalities. Radiological imaging, particularly the…

图像与视频处理 · 电气工程与系统科学 2023-06-16 Sultan Zavrak

By the start of 2020, the novel coronavirus disease (COVID-19) has been declared a worldwide pandemic. Because of the severity of this infectious disease, several kinds of research have focused on combatting its ongoing spread. One…

图像与视频处理 · 电气工程与系统科学 2021-05-19 Safa Ben Atitallah , Maha Driss , Wadii Boulila , Henda Ben Ghézala

The COVID-19 pandemic strained healthcare resources and prompted discussion about how machine learning can alleviate physician burdens and contribute to diagnosis. Chest x-rays (CXRs) are used for diagnosis of COVID-19, but few studies…

图像与视频处理 · 电气工程与系统科学 2025-03-03 Luis Lara , Lucia Eve Berger , Rajesh Raju

In this paper, we have trained several deep convolutional networks with introduced training techniques for classifying X-ray images into three classes: normal, pneumonia, and COVID-19, based on two open-source datasets. Our data contains…

图像与视频处理 · 电气工程与系统科学 2021-05-05 Mohammad Rahimzadeh , Abolfazl Attar

Coronavirus disease (COVID-19) is a pandemic disease, which has already caused thousands of causalities and infected several millions of people worldwide. Any technological tool enabling rapid screening of the COVID-19 infection with high…

Novel Coronavirus (COVID-19) has drastically overwhelmed more than 200 countries affecting millions and claiming almost 1 million lives, since its emergence in late 2019. This highly contagious disease can easily spread, and if not…

The challenge of imbalanced data is prominent in medical image classification. This challenge arises when there is a significant disparity in the number of images belonging to a particular class, such as the presence or absence of a…

计算机视觉与模式识别 · 计算机科学 2026-01-01 Sina Jahromi , Farshid Hajati , Alireza Rezaee , Javaher Nourian

Chest x-rays are a vital tool in the workup of many patients. Similar to most medical imaging modalities, they are profoundly multi-modal and are capable of visualising a variety of combinations of conditions. There is an ever pressing need…

图像与视频处理 · 电气工程与系统科学 2021-06-08 Bradley Segal , David M. Rubin , Grace Rubin , Adam Pantanowitz

Computed tomography (CT) imaging is a promising approach to diagnosing the COVID-19. Machine learning methods can be employed to train models from labeled CT images and predict whether a case is positive or negative. However, there exists…

图像与视频处理 · 电气工程与系统科学 2021-01-15 Yi Liu , Shuiwang Ji

The world is still overwhelmed by the spread of the COVID-19 virus. With over 250 Million infected cases as of November 2021 and affecting 219 countries and territories, the world remains in the pandemic period. Detecting COVID-19 using the…

图像与视频处理 · 电气工程与系统科学 2022-10-27 Gargi Desai , Nelly Elsayed , Zag Elsayed , Murat Ozer

The novel coronavirus universally known as the COVID-19 outbreak arises at the end of 2019 in one of the East Asian countries and it is subjected to widespread discussion and debate. There are almost 200 countries affected across the globe…

图像与视频处理 · 电气工程与系统科学 2024-03-13 Kinjal A Patel , Tanvi Goswami

The coronavirus disease 2019 (COVID-19) pandemic continues to have a tremendous impact on patients and healthcare systems around the world. In the fight against this novel disease, there is a pressing need for rapid and effective screening…

图像与视频处理 · 电气工程与系统科学 2020-09-14 Hayden Gunraj , Linda Wang , Alexander Wong

The Coronavirus Disease 2019 (COVID-19) has spread globally and caused serious damage. Chest X-ray images are widely used for COVID-19 diagnosis and the Artificial Intelligence method can increase efficiency and accuracy. In the Challenge…

图像与视频处理 · 电气工程与系统科学 2023-01-03 Juntao Jiang , Shuyi Lin

Background and Objective: Artificial intelligence (AI) methods coupled with biomedical analysis has a critical role during pandemics as it helps to release the overwhelming pressure from healthcare systems and physicians. As the ongoing…

图像与视频处理 · 电气工程与系统科学 2022-07-12 Aman Swaraj , Karan Verma

Deep learning is gaining instant popularity in computer aided diagnosis of COVID-19. Due to the high sensitivity of Computed Tomography (CT) to this disease, CT-based COVID-19 detection with visual models is currently at the forefront of…

计算机视觉与模式识别 · 计算机科学 2021-08-13 Fouzia Altaf , Syed M. S. Islam , Naveed Akhtar

Coronavirus disease 2019 (COVID-19) is a Public Health Emergency of International Concern infecting more than 40 million people across 188 countries and territories. Chest computed tomography (CT) imaging technique benefits from its high…

图像与视频处理 · 电气工程与系统科学 2021-02-02 Yifan Jiang , Han Chen , David K. Han , Hanseok Ko

Background: The COVID-19 pandemic has overwhelmed healthcare systems, emphasizing the need for AI-driven tools to assist in rapid and accurate patient prognosis. Chest X-ray imaging is a widely available diagnostic tool, but existing…

图像与视频处理 · 电气工程与系统科学 2025-03-18 Alfred Simbun , Suresh Kumar

The COVID-19 pandemic has been having a severe and catastrophic effect on humankind and is being considered the most crucial health calamity of the century. One of the best methods of detecting COVID-19 is from radiological images, namely…

图像与视频处理 · 电气工程与系统科学 2020-10-15 Arjun Sarkar , Joerg Vandenhirtz , Jozsef Nagy , David Bacsa , Mitchell Riley

Coronavirus disease 2019 (COVID-19) is one of the most destructive pandemic after millennium, forcing the world to tackle a health crisis. Automated lung infections classification using chest X-ray (CXR) images could strengthen diagnostic…

图像与视频处理 · 电气工程与系统科学 2021-01-11 Jingxiong Li , Yaqi Wang , Shuai Wang , Jun Wang , Jun Liu , Qun Jin , Lingling Sun