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Artificial intelligence-based analysis of lung ultrasound imaging has been demonstrated as an effective technique for rapid diagnostic decision support throughout the COVID-19 pandemic. However, such techniques can require days- or…

The global pandemic of the novel coronavirus disease 2019 (COVID-19) has put tremendous pressure on the medical system. Imaging plays a complementary role in the management of patients with COVID-19. Computed tomography (CT) and chest X-ray…

图像与视频处理 · 电气工程与系统科学 2021-12-21 Hui Che , Jared Radbel , Jag Sunderram , John L. Nosher , Vishal M. Patel , Ilker Hacihaliloglu

Ultrasound is fast becoming an inevitable diagnostic tool for regular and continuous monitoring of the lung with the recent outbreak of COVID-19. In this work, a novel approach is presented to extract acoustic propagation-based features to…

图像与视频处理 · 电气工程与系统科学 2021-06-15 Mahesh Raveendranatha Panicker , Yale Tung Chen , Gayathri M , Madhavanunni A N , Kiran Vishnu Narayan , C Kesavadas , A P Vinod

As a lightweight and non-invasive imaging technique, lung ultrasound (LUS) has gained importance for assessing lung pathologies. The use of Artificial intelligence (AI) in medical decision support systems is promising due to the time- and…

With the rapid development of COVID-19 into a global pandemic, there is an ever more urgent need for cheap, fast and reliable tools that can assist physicians in diagnosing COVID-19. Medical imaging such as CT can take a key role in…

图像与视频处理 · 电气工程与系统科学 2021-01-26 Jannis Born , Gabriel Brändle , Manuel Cossio , Marion Disdier , Julie Goulet , Jérémie Roulin , Nina Wiedemann

We describe a novel, two-stage computer assistance system for lung anomaly detection using ultrasound imaging in the intensive care setting to improve operator performance and patient stratification during coronavirus pandemics. The…

In the recent past with the rapid surge of COVID-19 infections, lung ultrasound has emerged as a fast and powerful diagnostic tool particularly for continuous and periodic monitoring of the lung. There have been many attempts towards…

图像与视频处理 · 电气工程与系统科学 2022-08-02 Anito Anto , Linda Rose Jimson , Tanya Rose , Mohammed Jafrin , Mahesh Raveendranatha Panicker

Novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a pandemic of epic proportions and a global response to prepare health systems worldwide is of utmost importance. In addition to its cost-effectiveness in a…

Lung ultrasound (LUS) is an important imaging modality used by emergency physicians to assess pulmonary congestion at the patient bedside. B-line artifacts in LUS videos are key findings associated with pulmonary congestion. Not only can…

Ultrasound (US) is a non-invasive yet effective medical diagnostic imaging technique for the COVID-19 global pandemic. However, due to complex feature behaviors and expensive annotations of US images, it is difficult to apply Artificial…

计算机视觉与模式识别 · 计算机科学 2021-03-02 Lei Liu , Wentao Lei , Yongfang Luo , Cheng Feng , Xiang Wan , Li Liu

The COVID-19 pandemic has affected millions of people globally, with respiratory organs being strongly affected in individuals with comorbidities. Medical imaging-based diagnosis and prognosis have become increasingly popular in clinical…

With the onset of the COVID-19 pandemic, ultrasound has emerged as an effective tool for bedside monitoring of patients. Due to this, a large amount of lung ultrasound scans have been made available which can be used for AI based diagnosis…

图像与视频处理 · 电气工程与系统科学 2022-01-20 Gautam Rajendrakumar Gare , Hai V. Tran , Bennett P deBoisblanc , Ricardo Luis Rodriguez , John Michael Galeotti

Understanding chest CT imaging of the coronavirus disease 2019 (COVID-19) will help detect infections early and assess the disease progression. Especially, automated severity assessment of COVID-19 in CT images plays an essential role in…

图像与视频处理 · 电气工程与系统科学 2020-05-26 Kelei He , Wei Zhao , Xingzhi Xie , Wen Ji , Mingxia Liu , Zhenyu Tang , Feng Shi , Yang Gao , Jun Liu , Junfeng Zhang , Dinggang Shen

Quantitative lung measures derived from computed tomography (CT) have been demonstrated to improve prognostication in coronavirus disease (COVID-19) patients, but are not part of the clinical routine since required manual segmentation of…

This paper proposes a semi-automatic system based on quantitative characterization of the specific image patterns in lung ultrasound (LUS) images, in order to assess the lung conditions of patients with COVID-19 pneumonia, as well as to…

医学物理 · 物理学 2021-11-05 Yuanyuan Wang , Yao Zhang , Qiong He , Hongen Liao , Jianwen Luo

Lung cancer poses a significant global public health challenge, emphasizing the importance of early detection for improved patient outcomes. Recent advancements in deep learning algorithms have shown promising results in medical image…

图像与视频处理 · 电气工程与系统科学 2023-05-26 Karthick Prasad Gunasekaran

This study presents a computer-aided diagnosis (CAD) system to assist early detection of lung metastases during endobronchial ultrasound (EBUS) procedures, significantly reducing follow-up time and enabling timely treatment. Due to limited…

图像与视频处理 · 电气工程与系统科学 2025-05-15 Ching-Kai Lin , Di-Chun Wei , Yun-Chien Cheng

Lung ultrasound (LUS) is an increasingly popular diagnostic imaging modality for continuous and periodic monitoring of lung infection, given its advantages of non-invasiveness, non-ionizing nature, portability and easy disinfection. The…

CT imaging is crucial for diagnosis, assessment and staging COVID-19 infection. Follow-up scans every 3-5 days are often recommended for disease progression. It has been reported that bilateral and peripheral ground glass opacification…

计算机视觉与模式识别 · 计算机科学 2020-12-01 Fei Shan , Yaozong Gao , Jun Wang , Weiya Shi , Nannan Shi , Miaofei Han , Zhong Xue , Dinggang Shen , Yuxin Shi

Computed Tomography (CT) scans provide a detailed image of the lungs, allowing clinicians to observe the extent of damage caused by COVID-19. The CT severity score (CTSS) based scoring method is used to identify the extent of lung…

图像与视频处理 · 电气工程与系统科学 2023-03-20 Anand Thyagachandran , Hema A Murthy
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