AIMC Topic: Lung

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Discriminating TB lung nodules from early lung cancers using deep learning.

BMC medical informatics and decision making Jun 21, 2022
BACKGROUND: In developing countries where both high rates of smoking and endemic tuberculosis (TB) are often present, identification of early lung cancer can be significantly confounded by the presence of nodules such as those due to latent TB (LTB)....
Humans Deep Learning Lung Neoplasms Tuberculosis Neural Networks, Computer Lung
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Lung-Optimized Deep-Learning-Based Reconstruction for Ultralow-Dose CT.

Academic radiology Jun 20, 2022
RATIONALE AND OBJECTIVES: To evaluate the image properties of lung-specialized deep-learning-based reconstruction (DLR) and its applicability in ultralow-dose CT (ULDCT) relative to hybrid- (HIR) and model-based iterative-reconstructions (MBIR).
Algorithms Tomography, X-Ray Computed Lung Humans Radiation Dosage Deep Learning Radiographic Image Interpretation, Computer-Assisted
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Novel COVID-19 Diagnosis Delivery App Using Computed Tomography Images Analyzed with Saliency-Preprocessing and Deep Learning.

Tomography (Ann Arbor, Mich.) Jun 20, 2022
This app project was aimed to remotely deliver diagnoses and disease-progression information to COVID-19 patients to help minimize risk during this and future pandemics. Data collected from chest computed tomography (CT) scans of COVID-19-infected pa...
COVID-19 Testing Deep Learning Mobile Applications COVID-19 Tomography, X-Ray Computed SARS-CoV-2 Lung Humans
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VCNet: Hybrid Deep Learning Model for Detection and Classification of Lung Carcinoma Using Chest Radiographs.

Frontiers in public health Jun 20, 2022
Detection of malignant lung nodules from Computed Tomography (CT) images is a significant task for radiologists. But, it is time-consuming in nature. Despite numerous breakthroughs in studies on the application of deep learning models for the identif...
Lung Neoplasms Lung Humans Carcinoma Deep Learning Tomography, X-Ray Computed
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An Enhanced Priori Knowledge GAN for CT Images Generation of Early Lung Nodules with Small-Size Labelled Samples.

Oxidative medicine and cellular longevity Jun 14, 2022
The small size of labelled samples is one of the challenging problems in identifying early lung nodules from CT images using deep learning methods. Recent literature on the topic shows that deep convolutional generative adversarial network (DCGAN) ha...
Lung Image Processing, Computer-Assisted Neural Networks, Computer Tomography, X-Ray Computed
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Editorial Comment: Artificial Intelligence for Lung Nodules-Progress, but Is It Enough?

AJR. American journal of roentgenology May 25, 2022
Lung Multiple Pulmonary Nodules Neural Networks, Computer Artificial Intelligence Humans
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Prediction of the position of external markers using a recurrent neural network trained with unbiased online recurrent optimization for safe lung cancer radiotherapy.

Computer methods and programs in biomedicine May 25, 2022
BACKGROUND AND OBJECTIVE: During lung cancer radiotherapy, the position of infrared reflective objects on the chest can be recorded to estimate the tumor location. However, radiotherapy systems have a latency inherent to robot control limitations tha...
Respiration Neural Networks, Computer Algorithms Lung Neoplasms Motion Lung Humans
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Development and Validation of a Risk Stratification Model of Pulmonary Ground-Glass Nodules Based on Complementary Lung-RADS 1.1 and Deep Learning Scores.

Frontiers in public health May 23, 2022
PURPOSE: To assess the value of novel deep learning (DL) scores combined with complementary lung imaging reporting and data system 1.1 (cLung-RADS 1.1) in managing the risk stratification of ground-glass nodules (GGNs) and therefore improving the eff...
Lung Neoplasms Multiple Pulmonary Nodules Humans Retrospective Studies Tomography, X-Ray Computed Lung Risk Assessment Deep Learning
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Eight pruning deep learning models for low storage and high-speed COVID-19 computed tomography lung segmentation and heatmap-based lesion localization: A multicenter study using COVLIAS 2.0.

Computers in biology and medicine May 21, 2022
BACKGROUND: COVLIAS 1.0: an automated lung segmentation was designed for COVID-19 diagnosis. It has issues related to storage space and speed. This study shows that COVLIAS 2.0 uses pruned AI (PAI) networks for improving both storage and speed, wilie...
COVID-19 Tomography, X-Ray Computed Reproducibility of Results Lung Humans Neural Networks, Computer COVID-19 Testing Deep Learning Image Processing, Computer-Assisted
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Treatment plan prediction for lung IMRT using deep learning based fluence map generation.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) May 21, 2022
PURPOSE: Recently, it has been shown that automated treatment planning can be executed by direct fluence prediction from patient anatomy using convolutional neural networks. Proof of principle publications utilise a fixed dose prescription and fixed ...
Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Deep Learning Lung Neoplasms Radiotherapy, Intensity-Modulated Humans Lung
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