Pulmonology

Large-scale investigation of deep learning approaches for ventilated lung segmentation using multi-nuclear hyperpolarized gas MRI.

Respiratory diseases are leading causes of mortality and morbidity worldwide. Pulmonary imaging is an essential component of the diagnosis, treatment planning, monitoring, and treatment assessment of respiratory diseases. Insights into numerous pulmonary pathologies can be gleaned from functional lung MRI techniques. These include hyperpolarized gas ventilation MRI, which enables visualization and...

CAM-Wnet: An effective solution for accurate pulmonary embolism segmentation.

BACKGROUND: The morbidity of pulmonary embolism (PE) is only lower than that of coronary heart disease and hypertension. Early detection, early diagnosis, and timely treatment are the keys to effectively reduce the risk of death. Nevertheless, PE segmentation is still a challenging task at present. The automatic segmentation of PE is particularly important. On the one hand, manual segmentation of ...

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

BACKGROUND: In developing countries where both high rates of smoking and endemic tuberculosis (TB) are often present, identification of early lung can...

Multisemantic Level Patch Merger Vision Transformer for Diagnosis of Pneumonia.

The most popular test for pneumonia, a serious health threat to children, is chest X-ray imaging. However, the diagnosis of pneumonia relies on the ex...

Lung-Optimized Deep-Learning-Based Reconstruction for Ultralow-Dose CT.

RATIONALE AND OBJECTIVES: To evaluate the image properties of lung-specialized deep-learning-based reconstruction (DLR) and its applicability in ultra...

Size-adaptive mediastinal multilesion detection in chest CT images via deep learning and a benchmark dataset.

PURPOSE: Many deep learning methods have been developed for pulmonary lesion detection in chest computed tomography (CT) images. However, these method...

Novel COVID-19 Diagnosis Delivery App Using Computed Tomography Images Analyzed with Saliency-Preprocessing and Deep Learning.

This app project was aimed to remotely deliver diagnoses and disease-progression information to COVID-19 patients to help minimize risk during this an...

VCNet: Hybrid Deep Learning Model for Detection and Classification of Lung Carcinoma Using Chest Radiographs.

Detection of malignant lung nodules from Computed Tomography (CT) images is a significant task for radiologists. But, it is time-consuming in nature. ...

Diagnostic performance of artificial intelligence approved for adults for the interpretation of pediatric chest radiographs.

Artificial intelligence (AI) applied to pediatric chest radiographs are yet scarce. This study evaluated whether AI-based software developed for adult...

A dataset of simulated patient-physician medical interviews with a focus on respiratory cases.

Artificial Intelligence (AI) is playing a major role in medical education, diagnosis, and outbreak detection through Natural Language Processing (NLP)...

Improved Analysis of COVID-19 Influenced Pneumonia from the Chest X-Rays Using Fine-Tuned Residual Networks.

COVID-19 has remained a threat to world life despite a recent reduction in cases. There is still a possibility that the virus will evolve and become m...

Impact of Artificial Intelligence Assistance on Chest CT Interpretation Times: A Prospective Randomized Study.

Deep learning-based convolutional neural networks have enabled major advances in development of artificial intelligence (AI) software applications. M...

Multi-branch fusion auxiliary learning for the detection of pneumonia from chest X-ray images.

Lung infections caused by bacteria and viruses are infectious and require timely screening and isolation, and different types of pneumonia require dif...

Vomiting Management and Effect Prediction after Early Chemotherapy of Lung Cancer with Diffusion-Weighted Imaging under Artificial Intelligence Algorithm and Comfort Care Intervention.

This aim of this research was to explore the evaluation and prediction value of diffusion-weighted imaging (DWI) under artificial intelligence algorit...

Deep Learning to Optimize Candidate Selection for Lung Cancer CT Screening: Advancing the 2021 USPSTF Recommendations.

Background A deep learning (DL) model to identify lung cancer screening candidates based on their chest radiographs requires external validation with ...

An Enhanced Priori Knowledge GAN for CT Images Generation of Early Lung Nodules with Small-Size Labelled Samples.

The small size of labelled samples is one of the challenging problems in identifying early lung nodules from CT images using deep learning methods. Re...

Enhancing PM Prediction Using NARX-Based Combined CNN and LSTM Hybrid Model.

In a world where humanity's interests come first, the environment is flooded with pollutants produced by humans' urgent need for expansion. Air pollut...

Performance Analysis of State-of-the-Art CNN Architectures for LUNA16.

The convolutional neural network (CNN) has become a powerful tool in machine learning (ML) that is used to solve complex problems such as image recogn...

Deep Learning-Based Digitally Reconstructed Tomography of the Chest in the Evaluation of Solitary Pulmonary Nodules: A Feasibility Study.

RATIONALE AND OBJECTIVES: Computed tomography (CT) is preferred for evaluating solitary pulmonary nodules (SPNs) but access or availability may be lac...

Oxygen delivery in pediatric cardiac surgery and its association with acute kidney injury using machine learning.

OBJECTIVE: Acute kidney injury (AKI) after pediatric cardiac surgery with cardiopulmonary bypass (CPB) is a frequently reported complication. In this ...