AIMC Topic: Lung
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COVID-19 Diagnosis Using an Enhanced Inception-ResNetV2 Deep Learning Model in CXR Images.
Journal of healthcare engineering
Jun 3, 2021
The COVID-19 pandemic has a significant negative effect on people's health, as well as on the world's economy. Polymerase chain reaction (PCR) is one of the main tests used to detect COVID-19 infection. However, it is expensive, time-consuming, and l...
Enhanced Diagnosis of Pneumothorax with an Improved Real-Time Augmentation for Imbalanced Chest X-rays Data Based on DCNN.
IEEE/ACM transactions on computational biology and bioinformatics
Jun 3, 2021
Pneumothorax is a common pulmonary disease that can lead to dyspnea and can be life-threatening. X-ray examination is the main means to diagnose this disease. Computer-aided diagnosis of pneumothorax on chest X-ray, as a prerequisite for a timely cur...
Learning Tubule-Sensitive CNNs for Pulmonary Airway and Artery-Vein Segmentation in CT.
IEEE transactions on medical imaging
Jun 1, 2021
Training convolutional neural networks (CNNs) for segmentation of pulmonary airway, artery, and vein is challenging due to sparse supervisory signals caused by the severe class imbalance between tubular targets and background. We present a CNNs-based...
Prediction of the motion of chest internal points using a recurrent neural network trained with real-time recurrent learning for latency compensation in lung cancer radiotherapy.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
May 28, 2021
During the radiotherapy treatment of patients with lung cancer, the radiation delivered to healthy tissue around the tumor needs to be minimized, which is difficult because of respiratory motion and the latency of linear accelerator (LINAC) systems. ...
Deep learning predicts cardiovascular disease risks from lung cancer screening low dose computed tomography.
Nature communications
May 20, 2021
Cancer patients have a higher risk of cardiovascular disease (CVD) mortality than the general population. Low dose computed tomography (LDCT) for lung cancer screening offers an opportunity for simultaneous CVD risk estimation in at-risk patients. Ou...
Aged
Aged, 80 and over
Adult
Follow-Up Studies
Male
Datasets as Topic
Cardiovascular Diseases
Coronary Vessels
Middle Aged
Clinical Trials as Topic
Retrospective Studies
Risk Assessment
Humans
Tomography, X-Ray Computed
Female
Lung
Risk Factors
Deep Learning
ROC Curve
Image Processing, Computer-Assisted
Lung Neoplasms
Electrocardiography
Mass Screening
Performance and reading time of lung nodule identification on multidetector CT with or without an artificial intelligence-powered computer-aided detection system.
Clinical radiology
May 19, 2021
AIM: To compare the performance and reading time of different readers using automatic artificial intelligence (AI)-powered computer-aided detection (CAD) to detect lung nodules in different reading modes.
Quantitative evaluation of COVID-19 pneumonia severity by CT pneumonia analysis algorithm using deep learning technology and blood test results.
Japanese journal of radiology
May 14, 2021
PURPOSE: To evaluate whether early chest computed tomography (CT) lesions quantified by an artificial intelligence (AI)-based commercial software and blood test values at the initial presentation can differentiate the severity of COVID-19 pneumonia.
A self-supervised feature-standardization-block for cross-domain lung disease classification.
Methods (San Diego, Calif.)
May 13, 2021
With the advance of deep learning technology, convolutional neural network (CNN) has been wildly used and achieved the state-of-the-art performances in the area of medical image classification. However, most existing medical image classification meth...
Augmenting lung cancer diagnosis on chest radiographs: positioning artificial intelligence to improve radiologist performance.
Clinical radiology
May 11, 2021
AIM: To evaluate the role that artificial intelligence (AI) could play in assisting radiologists as the first reader of chest radiographs (CXRs), to increase the accuracy and efficiency of lung cancer diagnosis by flagging positive cases before passi...
Hybrid dilation and attention residual U-Net for medical image segmentation.
Computers in biology and medicine
May 11, 2021
Medical image segmentation is a typical task in medical image processing and critical foundation in medical image analysis. U-Net is well-liked in medical image segmentation, but it doesn't fully explore useful features of the channel and capitalize ...
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