AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Thorax

Showing 81 to 90 of 220 articles

Clear Filters

Using Radiomics as Prior Knowledge for Thorax Disease Classification and Localization in Chest X-rays.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Chest X-ray becomes one of the most common medical diagnoses due to its noninvasiveness. The number of chest X-ray images has skyrocketed, but reading chest X-rays still have been manually performed by radiologists, which creates huge burnouts and de...

Automatic contouring of normal tissues with deep learning for preclinical radiation studies.

Physics in medicine and biology
Delineation of relevant normal tissues is a bottleneck in image-guided precision radiotherapy workflows for small animals. A deep learning (DL) model for automatic contouring using standardized 3D micro cone-beam CT (CBCT) volumes as input is propose...

Deep learning-based segmentation of the thorax in mouse micro-CT scans.

Scientific reports
For image-guided small animal irradiations, the whole workflow of imaging, organ contouring, irradiation planning, and delivery is typically performed in a single session requiring continuous administration of anaesthetic agents. Automating contourin...

Effective deep learning approaches for predicting COVID-19 outcomes from chest computed tomography volumes.

Scientific reports
The rapid evolution of the novel coronavirus disease (COVID-19) pandemic has resulted in an urgent need for effective clinical tools to reduce transmission and manage severe illness. Numerous teams are quickly developing artificial intelligence appro...

E-TBNet: Light Deep Neural Network for Automatic Detection of Tuberculosis with X-ray DR Imaging.

Sensors (Basel, Switzerland)
Currently, the tuberculosis (TB) detection model based on chest X-ray images has the problem of excessive reliance on hardware computing resources, high equipment performance requirements, and being harder to deploy in low-cost personal computer and ...

Objective evaluation of deep uncertainty predictions for COVID-19 detection.

Scientific reports
Deep neural networks (DNNs) have been widely applied for detecting COVID-19 in medical images. Existing studies mainly apply transfer learning and other data representation strategies to generate accurate point estimates. The generalization power of ...

Detection of COVID-19 With CT Images Using Hybrid Complex Shearlet Scattering Networks.

IEEE journal of biomedical and health informatics
With the ongoing worldwide coronavirus disease 2019 (COVID-19) pandemic, it is desirable to develop effective algorithms to automatically detect COVID-19 with chest computed tomography (CT) images. Recently, a considerable number of methods based on ...

Coarse-to-fine airway segmentation using multi information fusion network and CNN-based region growing.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Automatic airway segmentation from chest computed tomography (CT) scans plays an important role in pulmonary disease diagnosis and computer-assisted therapy. However, low contrast at peripheral branches and complex tree-lik...

Analysis of high-resolution reconstruction of medical images based on deep convolutional neural networks in lung cancer diagnostics.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: To study the diagnostic effect of 64-slice spiral CT and MRI high-resolution images based on deep convolutional neural networks(CNN) in lung cancer.

TBNet: a context-aware graph network for tuberculosis diagnosis.

Computer methods and programs in biomedicine
Tuberculosis (TB) is an infectious bacterial disease. It can affect the human lungs, brain, bones, and kidneys. Pulmonary tuberculosis is the most common. This airborne bacterium can be transmitted with the droplets by coughing and sneezing. So far, ...