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Lung

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GraphRegNet: Deep Graph Regularisation Networks on Sparse Keypoints for Dense Registration of 3D Lung CTs.

IEEE transactions on medical imaging
In the last two years learning-based methods have started to show encouraging results in different supervised and unsupervised medical image registration tasks. Deep neural networks enable (near) real time applications through fast inference times an...

A survey of computer-aided diagnosis of lung nodules from CT scans using deep learning.

Computers in biology and medicine
Lung cancer has one of the highest mortalities of all cancers. According to the National Lung Screening Trial, patients who underwent low-dose computed tomography (CT) scanning once a year for 3 years showed a 20% decline in lung cancer mortality. To...

Synthetic pulmonary perfusion images from 4DCT for functional avoidance using deep learning.

Physics in medicine and biology
To develop and evaluate the performance of a deep learning model to generate synthetic pulmonary perfusion images from clinical 4DCT images for patients undergoing radiotherapy for lung cancer.. A clinical data set of 58 pre- and post-radiotherapyTc-...

Evaluation of the Effectiveness of Artificial Intelligence Chest CT Lung Nodule Detection Based on Deep Learning.

Journal of healthcare engineering
Lung cancer is one of the most malignant tumors. If it can be detected early and treated actively, it can effectively improve a patient's survival rate. Therefore, early diagnosis of lung cancer is very important. Early-stage lung cancer usually appe...

Deep-learning based detection of COVID-19 using lung ultrasound imagery.

PloS one
BACKGROUND: The COVID-19 pandemic has exposed the vulnerability of healthcare services worldwide, especially in underdeveloped countries. There is a clear need to develop novel computer-assisted diagnosis tools to provide rapid and cost-effective scr...

A bagging dynamic deep learning network for diagnosing COVID-19.

Scientific reports
COVID-19 is a serious ongoing worldwide pandemic. Using X-ray chest radiography images for automatically diagnosing COVID-19 is an effective and convenient means of providing diagnostic assistance to clinicians in practice. This paper proposes a bagg...

Scalable quorum-based deep neural networks with adversarial learning for automated lung lobe segmentation in fast helical free-breathing CTs.

International journal of computer assisted radiology and surgery
PURPOSE: Fast helical free-breathing CT (FHFBCT) scans are widely used for 5DCT and 5D Cone Beam imaging protocols. For quantitative analysis of lung physiology and function, it is important to segment the lung lobes in these scans. Since the 5DCT pr...

Validating deep learning inference during chest X-ray classification for COVID-19 screening.

Scientific reports
The new coronavirus unleashed a worldwide pandemic in early 2020, and a fatality rate several times that of the flu. As the number of infections soared, and capabilities for testing lagged behind, chest X-ray (CXR) imaging became more relevant in the...

Deep learning and lung ultrasound for Covid-19 pneumonia detection and severity classification.

Computers in biology and medicine
The Covid-19 European outbreak in February 2020 has challenged the world's health systems, eliciting an urgent need for effective and highly reliable diagnostic instruments to help medical personnel. Deep learning (DL) has been demonstrated to be use...