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This technical report proposes the use of a deep convolutional neural network as a preliminary diagnostic method in the analysis of chest computed tomography images from patients with symptoms of Severe Acute Respiratory Syndrome (SARS) and…

图像与视频处理 · 电气工程与系统科学 2022-08-24 Victor Felipe Reis-Silva

Covid-19 is a very serious deadly disease that has been announced as a pandemic by the world health organization (WHO). The whole world is working with all its might to end Covid-19 pandemic, which puts countries in serious health and…

图像与视频处理 · 电气工程与系统科学 2020-12-11 Ali Narin

The infectious disease caused by novel corona virus (2019-nCoV) has been widely spreading since last year and has shaken the entire world. It has caused an unprecedented effect on daily life, global economy and public health. Hence this…

图像与视频处理 · 电气工程与系统科学 2024-08-28 Alloy Das , Rohit Agarwal , Rituparna Singh , Arindam Chowdhury , Debashis Nandi

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

Since this COVID-19 pandemic thrives, the utilization of X-Ray images of the Chest (CXR) as a complementary screening technique to RT-PCR testing grows to its clinical use for respiratory complaints. Many new deep learning approaches have…

图像与视频处理 · 电气工程与系统科学 2021-09-07 Md Gulzar Hussain , Ye Shiren

The significance of efficient and accurate diagnosis amidst the unique challenges posed by the COVID-19 pandemic underscores the urgency for innovative approaches. In response to these challenges, we propose a transfer learning-based…

图像与视频处理 · 电气工程与系统科学 2023-12-12 Kenan Morani , Esra Kaya Ayana , Devrim Unay

With increasing number of COVID-19 cases globally, all the countries are ramping up the testing numbers. While the RT-PCR kits are available in sufficient quantity in several countries, others are facing challenges with limited availability…

图像与视频处理 · 电气工程与系统科学 2020-08-10 Aakarsh Malhotra , Surbhi Mittal , Puspita Majumdar , Saheb Chhabra , Kartik Thakral , Mayank Vatsa , Richa Singh , Santanu Chaudhury , Ashwin Pudrod , Anjali Agrawal

The rapid outbreak of COVID-19 threatens humans life all around the world. Due to insufficient diagnostic infrastructures, developing an accurate, efficient, inexpensive, and quick diagnostic tool is of great importance. As chest…

图像与视频处理 · 电气工程与系统科学 2021-01-01 Maryam Dialameh , Ali Hamzeh , Hossein Rahmani , Amir Reza Radmard , Safoura Dialameh

In this study, a dataset of X-ray images from patients with common viral pneumonia, bacterial pneumonia, confirmed Covid-19 disease was utilized for the automatic detection of the Coronavirus disease. The point of the investigation is to…

图像与视频处理 · 电气工程与系统科学 2021-10-19 Sarath Pathari

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…

The novel coronavirus disease (COVID-19) constitutes a public health emergency globally. It is a deadly disease which has infected more than 230 million people worldwide. Therefore, early and unswerving detection of COVID-19 is necessary.…

图像与视频处理 · 电气工程与系统科学 2022-12-22 Aeyan Ashraf , Asad Malik , Zahid Khan

The novel coronavirus (COVID-19), a highly infectious respiratory disease caused by the SARS-CoV-2 has emerged as an unprecedented healthcare crisis. The pandemic had a devastating impact on the health, well-being, and economy of the global…

图像与视频处理 · 电气工程与系统科学 2024-05-14 Sonit Singh

With the spread of COVID-19 around the globe over the past year, the usage of artificial intelligence (AI) algorithms and image processing methods to analyze the X-ray images of patients' chest with COVID-19 has become essential. The…

图像与视频处理 · 电气工程与系统科学 2025-01-16 Xinyuan Song

Deep Learning has achieved state of the art performance in medical imaging. However, these methods for disease detection focus exclusively on improving the accuracy of classification or predictions without quantifying uncertainty in a…

图像与视频处理 · 电气工程与系统科学 2020-03-30 Biraja Ghoshal , Allan Tucker

COVID-19 classification using chest Computed Tomography (CT) has been found pragmatically useful by several studies. Due to the lack of annotated samples, these studies recommend transfer learning and explore the choices of pre-trained…

计算机视觉与模式识别 · 计算机科学 2021-02-17 Fouzia Altaf , Syed M. S. Islam , Naeem K. Janjua , Naveed Akhtar

Coronavirus disease 2019 (COVID-19) is an infectious disease with first symptoms similar to the flu. COVID-19 appeared first in China and very quickly spreads to the rest of the world, causing then the 2019-20 coronavirus pandemic. In many…

图像与视频处理 · 电气工程与系统科学 2020-04-08 Karim Hammoudi , Halim Benhabiles , Mahmoud Melkemi , Fadi Dornaika , Ignacio Arganda-Carreras , Dominique Collard , Arnaud Scherpereel

There is a necessity to develop affordable, and reliable diagnostic tools, which allow containing the COVID-19 spreading. Machine Learning (ML) algorithms have been proposed to design support decision-making systems to assess chest X-ray…

COVID-19, due to its accelerated spread has brought in the need to use assistive tools for faster diagnosis in addition to typical lab swab testing. Chest X-Rays for COVID cases tend to show changes in the lungs such as ground glass…

图像与视频处理 · 电气工程与系统科学 2020-10-27 Gayathiri Murugamoorthy , Naimul Khan

Importance: An artificial intelligence (AI)-based model to predict COVID-19 likelihood from chest x-ray (CXR) findings can serve as an important adjunct to accelerate immediate clinical decision making and improve clinical decision making.…

The current pandemic, caused by the outbreak of a novel coronavirus (COVID-19) in December 2019, has led to a global emergency that has significantly impacted economies, healthcare systems and personal wellbeing all around the world.…

图像与视频处理 · 电气工程与系统科学 2021-01-19 Xiaocong Chen , Lina Yao , Tao Zhou , Jinming Dong , Yu Zhang