English
Related papers

Related papers: Full-scale Deeply Supervised Attention Network for…

200 papers

Automatic lesion segmentation on thoracic CT enables rapid quantitative analysis of lung involvement in COVID-19 infections. However, obtaining a large amount of voxel-level annotations for training segmentation networks is prohibitively…

Image and Video Processing · Electrical Eng. & Systems 2021-11-22 Weiyi Xie , Colin Jacobs , Jean-Paul Charbonnier , Bram van Ginneken

Deep learning-based medical image segmentation technology aims at automatic recognizing and annotating objects on the medical image. Non-local attention and feature learning by multi-scale methods are widely used to model network, which…

Computer Vision and Pattern Recognition · Computer Science 2020-12-08 Bo Wang , Lei Wang , Junyang Chen , Zhenghua Xu , Thomas Lukasiewicz , Zhigang Fu

The rapid spread of COVID-19 has necessitated efficient and accurate diagnostic methods. Computed Tomography (CT) scan images have emerged as a valuable tool for detecting the disease. In this article, we present a novel deep learning…

Image and Video Processing · Electrical Eng. & Systems 2023-08-15 Susmita Ghosh , Abhiroop Chatterjee

Accurate lung nodule segmentation is crucial for early-stage lung cancer diagnosis, as it can substantially enhance patient survival rates. Computed tomography (CT) images are widely employed for early diagnosis in lung nodule analysis.…

Image and Video Processing · Electrical Eng. & Systems 2025-08-11 Muhammad Usman , Azka Rehman , Abd Ur Rehman , Abdullah Shahid , Tariq Mahmood Khan , Imran Razzak , Minyoung Chung , Yeong Gil Shin

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…

Image and Video Processing · Electrical Eng. & Systems 2021-01-11 Jingxiong Li , Yaqi Wang , Shuai Wang , Jun Wang , Jun Liu , Qun Jin , Lingling Sun

COVID-19 is a global health problem. Consequently, early detection and analysis of the infection patterns are crucial for controlling infection spread as well as devising a treatment plan. This work proposes a two-stage deep Convolutional…

Image and Video Processing · Electrical Eng. & Systems 2020-09-21 Saddam Hussain Khan , Anabia Sohail , Asifullah Khan , Yeon Soo Lee

The novel Coronavirus disease (COVID-19) is a highly contagious virus and has spread all over the world, posing an extremely serious threat to all countries. Automatic lung infection segmentation from computed tomography (CT) plays an…

Image and Video Processing · Electrical Eng. & Systems 2021-07-29 Yichi Zhang , Qingcheng Liao , Lin Yuan , He Zhu , Jiezhen Xing , Jicong Zhang

Accurate segmentation of COVID-19 CT images is crucial for reducing the severity and mortality rates associated with COVID-19 infections. In response to blurred boundaries and high variability characteristic of lesion areas in COVID-19 CT…

Image and Video Processing · Electrical Eng. & Systems 2024-03-05 Jiao Ding , Jie Chang , Renrui Han , Li Yang

The recent outbreak of COVID-19 has led to urgent needs for reliable diagnosis and management of SARS-CoV-2 infection. As a complimentary tool, chest CT has been shown to be able to reveal visual patterns characteristic for COVID-19, which…

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…

Image and Video Processing · Electrical Eng. & Systems 2020-10-08 Xuelin Qian , Huazhu Fu , Weiya Shi , Tao Chen , Yanwei Fu , Fei Shan , Xiangyang Xue

In recent years, there has been a notable increase in the level of attention that is given to algorithms based on deep learning in the context of medical image segmentation. Nevertheless, the reliability of the field has been hindered due…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Sarmad Khan , Arslan Shaukat , Umer Asgher , Basim Azam

COVID-19, a new strain of coronavirus disease, has been one of the most serious and infectious disease in the world. Chest CT is essential in prognostication, diagnosing this disease, and assessing the complication. In this paper, a…

Image and Video Processing · Electrical Eng. & Systems 2021-09-22 Ziyang Wang , Irina Voiculescu

The novel coronavirus disease 2019 (COVID-19) characterized by atypical pneumonia has caused millions of deaths worldwide. Automatically segmenting lesions from chest Computed Tomography (CT) is a promising way to assist doctors in COVID-19…

Image and Video Processing · Electrical Eng. & Systems 2021-07-09 Yanwen Li , Luyang Luo , Huangjing Lin , Hao Chen , Pheng-Ann Heng

Airway segmentation is crucial for the examination, diagnosis, and prognosis of lung diseases, while its manual delineation is unduly burdensome. To alleviate this time-consuming and potentially subjective manual procedure, researchers have…

Image and Video Processing · Electrical Eng. & Systems 2022-09-12 Yang Nan , Javier Del Ser , Zeyu Tang , Peng Tang , Xiaodan Xing , Yingying Fang , Francisco Herrera , Witold Pedrycz , Simon Walsh , Guang Yang

The capability of generalization to unseen domains is crucial for deep learning models when considering real-world scenarios. However, current available medical image datasets, such as those for COVID-19 CT images, have large variations of…

Image and Video Processing · Electrical Eng. & Systems 2021-04-21 Qiangguo Jin , Hui Cui , Changming Sun , Zhaopeng Meng , Leyi Wei , Ran Su

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…

Image and Video Processing · Electrical Eng. & Systems 2022-02-25 Faeze Gholamian Khah , Samaneh Mostafapour , Seyedjafar Shojaerazavi , Nouraddin Abdi-Goushbolagh , Hossein Arabi

Liver lesion segmentation is a difficult yet critical task for medical image analysis. Recently, deep learning based image segmentation methods have achieved promising performance, which can be divided into three categories: 2D, 2.5D and…

Computer Vision and Pattern Recognition · Computer Science 2019-03-29 Xueying Chen , Rong Zhang , Pingkun Yan

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…

Image and Video Processing · Electrical Eng. & Systems 2025-06-24 Basma Jumaa Saleh , Zaid Omar , Vikrant Bhateja , Lila Iznita Izhar

A fully automatic technique for segmenting the liver and localizing its unhealthy tissues is a convenient tool in order to diagnose hepatic diseases and assess the response to the according treatments. In this work we propose a method to…

Computer Vision and Pattern Recognition · Computer Science 2017-12-01 Miriam Bellver , Kevis-Kokitsi Maninis , Jordi Pont-Tuset , Xavier Giro-i-Nieto , Jordi Torres , Luc Van Gool

In the last three years, the world has been facing a global crisis caused by Covid-19 pandemic. Medical imaging has been playing a crucial role in the fighting against this disease and saving the human lives. Indeed, CT-scans has proved…

Image and Video Processing · Electrical Eng. & Systems 2023-03-29 Fares Bougourzi , Cosimo Distante , Fadi Dornaika , Abdelmalik Taleb-Ahmed