AIMC Topic: Lung
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A Soft Robot for Peripheral Lung Cancer Diagnosis and Therapy.
Soft robotics
Aug 6, 2021
Lung cancer is one of the deadliest forms of cancers and is often diagnosed by performing biopsies with the use of a bronchoscope. However, this diagnostic procedure is limited in ability to explore deep into the periphery of the lung where cancer ca...
CNN-MoE Based Framework for Classification of Respiratory Anomalies and Lung Disease Detection.
IEEE journal of biomedical and health informatics
Aug 5, 2021
This paper presents and explores a robust deep learning framework for auscultation analysis. This aims to classify anomalies in respiratory cycles and detect diseases, from respiratory sound recordings. The framework begins with front-end feature ext...
Deep Learning to Determine the Activity of Pulmonary Tuberculosis on Chest Radiographs.
Radiology
Aug 3, 2021
Background Determining the activity of pulmonary tuberculosis on chest radiographs is difficult. Purpose To develop a deep learning model to identify active pulmonary tuberculosis on chest radiographs. Materials and Methods Chest radiographs were ret...
A novel strategy to develop deep learning for image super-resolution using original ultra-high-resolution computed tomography images of lung as training dataset.
Japanese journal of radiology
Jul 28, 2021
PURPOSE: To improve the image quality of inflated fixed cadaveric human lungs by utilizing ultra-high-resolution computed tomography (U-HRCT) as a training dataset for super-resolution processing using deep learning (SR-DL).
Attention-RefNet: Interactive Attention Refinement Network for Infected Area Segmentation of COVID-19.
IEEE journal of biomedical and health informatics
Jul 27, 2021
COVID-19 pneumonia is a disease that causes an existential health crisis in many people by directly affecting and damaging lung cells. The segmentation of infected areas from computed tomography (CT) images can be used to assist and provide useful in...
A Deep Learning Radiomics Model to Identify Poor Outcome in COVID-19 Patients With Underlying Health Conditions: A Multicenter Study.
IEEE journal of biomedical and health informatics
Jul 27, 2021
OBJECTIVE: Coronavirus disease 2019 (COVID-19) has caused considerable morbidity and mortality, especially in patients with underlying health conditions. A precise prognostic tool to identify poor outcomes among such cases is desperately needed.
COVID-19 Automatic Diagnosis With Radiographic Imaging: Explainable Attention Transfer Deep Neural Networks.
IEEE journal of biomedical and health informatics
Jul 27, 2021
Researchers seek help from deep learning methods to alleviate the enormous burden of reading radiological images by clinicians during the COVID-19 pandemic. However, clinicians are often reluctant to trust deep models due to their black-box character...
Self-supervised deep learning model for COVID-19 lung CT image segmentation highlighting putative causal relationship among age, underlying disease and COVID-19.
Journal of translational medicine
Jul 26, 2021
BACKGROUND: Coronavirus disease 2019 (COVID-19) is very contagious. Cases appear faster than the available Polymerase Chain Reaction test kits in many countries. Recently, lung computerized tomography (CT) has been used as an auxiliary COVID-19 testi...
Recognition of honeycomb lung in CT images based on improved MobileNet model.
Medical physics
Jul 17, 2021
PURPOSE: The research is to improve the efficiency and accuracy of recognition of honeycomb lung in CT images.
Value of a deep learning-based algorithm for detecting Lung-RADS category 4 nodules on chest radiographs in a health checkup population: estimation of the sample size for a randomized controlled trial.
European radiology
Jul 15, 2021
OBJECTIVE: To explore the value of a deep learning-based algorithm in detecting Lung CT Screening Reporting and Data System category 4 nodules on chest radiographs from an asymptomatic health checkup population.
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