AIMC Topic: Lung
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Analysis of segmentation of lung parenchyma based on deep learning methods.
Journal of X-ray science and technology
Jan 1, 2021
Precise segmentation of lung parenchyma is essential for effective analysis of the lung. Due to the obvious contrast and large regional area compared to other tissues in the chest, lung tissue is less difficult to segment. Special attention to detail...
Deep Learning Analysis in Prediction of COVID-19 Infection Status Using Chest CT Scan Features.
Advances in experimental medicine and biology
Jan 1, 2021
Background and aims Non-contrast chest computed tomography (CT) scanning is one of the important tools for evaluating of lung lesions. The aim of this study was to use a deep learning approach for predicting the outcome of patients with COVID-19 into...
Temporal changes of quantitative CT findings from 102 patients with COVID-19 in Wuhan, China: A longitudinal study.
Technology and health care : official journal of the European Society for Engineering and Medicine
Jan 1, 2021
BACKGROUND: Computed tomography (CT) imaging combined with artificial intelligence is important in the diagnosis and prognosis of lung diseases.
Detection of Lung Cancer on Computed Tomography Using Artificial Intelligence Applications Developed by Deep Learning Methods and the Contribution of Deep Learning to the Classification of Lung Carcinoma.
Current medical imaging
Jan 1, 2021
BACKGROUND: Every year, lung cancer contributes to a high percentage deaths in the world. Early detection of lung cancer is important for its effective treatment, and non-invasive rapid methods are usually used for diagnosis.
Using artificial intelligence to assist radiologists in distinguishing COVID-19 from other pulmonary infections.
Journal of X-ray science and technology
Jan 1, 2021
BACKGROUND: Accurate and rapid diagnosis of coronavirus disease (COVID-19) is crucial for timely quarantine and treatment.
Deep-LUMEN assay - human lung epithelial spheroid classification from brightfield images using deep learning.
Lab on a chip
Dec 15, 2020
Three-dimensional (3D) tissue models such as epithelial spheroids or organoids have become popular for pre-clinical drug studies. In contrast to 2D monolayer culture, the characterization of 3D tissue models from non-invasive brightfield images is a ...
[Effect of moxa-cone moxibustion at lung's back- points and front- points on Th17/Treg balance in mice with asthma].
Zhongguo zhen jiu = Chinese acupuncture & moxibustion
Nov 12, 2020
OBJECTIVE: To observe the effect of moxa-cone moxibustion at lung's back- points and front- points on the expression of helper T lymphocyte 17 (Th 17)/regulatory T lymphocyte (Treg) in mice with asthma, and to explore the possible mechanism of moxa-c...
Rapid tissue oxygenation mapping from snapshot structured-light images with adversarial deep learning.
Journal of biomedical optics
Nov 1, 2020
SIGNIFICANCE: Spatial frequency-domain imaging (SFDI) is a powerful technique for mapping tissue oxygen saturation over a wide field of view. However, current SFDI methods either require a sequence of several images with different illumination patter...
Deep learning applications to combat the dissemination of COVID-19 disease: a review.
European review for medical and pharmacological sciences
Nov 1, 2020
Recent Coronavirus (COVID-19) is one of the respiratory diseases, and it is known as fast infectious ability. This dissemination can be decelerated by diagnosing and quarantining patients with COVID-19 at early stages, thereby saving numerous lives. ...
Detection of COVID-19 Using Deep Learning Algorithms on Chest Radiographs.
Journal of thoracic imaging
Nov 1, 2020
PURPOSE: To evaluate the performance of a deep learning (DL) algorithm for the detection of COVID-19 on chest radiographs (CXR).
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