Quantitative CT texture-based method to predict diagnosis and prognosis of fibrosing interstitial lung disease patterns [PDF]
arXiv, 2022 Purpose: To utilize high-resolution quantitative CT (QCT) imaging features for prediction of diagnosis and prognosis in fibrosing interstitial lung diseases (ILD). Approach: 40 ILD patients (20 usual interstitial pneumonia (UIP), 20 non-UIP pattern ILD) were classified by expert consensus of 2 radiologists and followed for 7 years.
arxiv
Automatic classification between COVID-19 pneumonia, non-COVID-19 pneumonia, and the healthy on chest X-ray image: combination of data augmentation methods [PDF]
Sci Rep 10, 17532 (2020), 2020 Purpose: This study aimed to develop and validate computer-aided diagnosis (CXDx) system for classification between COVID-19 pneumonia, non-COVID-19 pneumonia, and the healthy on chest X-ray (CXR) images. Materials and Methods: From two public datasets, 1248 CXR images were obtained, which included 215, 533, and 500 CXR images of COVID-19 pneumonia ...
arxiv +1 more source
Distributed Multirobot Control for Non-Cooperative Herding [PDF]
arXiv, 2023 In this paper, we consider the problem of protecting a high-value area from being breached by sheep agents by crafting motions for dog robots. We use control barrier functions to pose constraints on the dogs' velocities that induce repulsion in the sheep relative to the high-value area.
arxiv
Deep Pneumonia: Attention-Based Contrastive Learning for Class-Imbalanced Pneumonia Lesion Recognition in Chest X-rays [PDF]
arXiv, 2022 Computer-aided X-ray pneumonia lesion recognition is important for accurate diagnosis of pneumonia. With the emergence of deep learning, the identification accuracy of pneumonia has been greatly improved, but there are still some challenges due to the fuzzy appearance of chest X-rays.
arxiv
Prediction of Pneumonia and COVID-19 Using Deep Neural Networks [PDF]
arXiv, 2023 Pneumonia, caused by bacteria and viruses, is a rapidly spreading viral infection with global implications. Prompt identification of infected individuals is crucial for containing its transmission. This study explores the potential of medical image analysis to address this challenge.
arxiv
Lung Ultrasound Segmentation and Adaptation between COVID-19 and Community-Acquired Pneumonia [PDF]
arXiv, 2021 Lung ultrasound imaging has been shown effective in detecting typical patterns for interstitial pneumonia, as a point-of-care tool for both patients with COVID-19 and other community-acquired pneumonia (CAP). In this work, we focus on the hyperechoic B-line segmentation task.
arxiv
Noncooperative Herding With Control Barrier Functions: Theory and Experiments [PDF]
arXiv, 2022 In this paper, we consider the problem of protecting a high-value unit from inadvertent attack by a group of agents using defending robots. Specifically, we develop a control strategy for the defending agents that we call "dog robots" to prevent a flock of "sheep agents" from breaching a protected zone.
arxiv
Route Design in Sheepdog System--Traveling Salesman Problem Formulation and Evolutionary Computation Solution-- [PDF]
arXiv, 2023 In this study, we consider the guidance control problem of the sheepdog system, which involves the guidance of the flock using the characteristics of the sheepdog and sheep. Sheepdog systems require a strategy to guide sheep agents to a target value using a small number of sheepdog agents, and various methods have been proposed.
arxiv
Early Diagnosis of Pneumonia with Deep Learning [PDF]
arXiv, 2019 Pneumonia has been one of the fatal diseases and has the potential to result in severe consequences within a short period of time, due to the flow of fluid in lungs, which leads to drowning. If not acted upon by drugs at the right time, pneumonia may result in death of individuals.
arxiv
Sheep identity recognition, age and weight estimation datasets [PDF]
arXiv, 2018 Increased interest of scientists, producers and consumers in sheep identification has been stimulated by the dramatic increase in population and the urge to increase productivity. The world population is expected to exceed 9.6 million in 2050. For this reason, awareness is raised towards the necessity of effective livestock production.
arxiv