Chest radiograph

A chest radiograph, called a chest X-ray (CXR), or chest film, is a projection radiograph of the chest used to diagnose conditions affecting the chest, its contents, and nearby structures. Chest radiographs are the most common film taken in medicine. Like all methods of radiography, chest radiography employs ionizing radiation in the form of X-rays to generate images of the chest. The mean radiation dose to an adult from a chest radiograph is around 0.02 mSv (2 mrem) for a front view (PA, or posteroanterior) and 0.08 mSv (8 mrem) for a side view (LL, or latero-lateral). Together, this corresponds to a background radiation equivalent time of about 10 days. Conditions commonly identified by chest radiography Pneumonia Pneumothorax Interstitial lung disease Heart failure Bone fracture Hiatal hernia Pulmonary tuberculosis Chest radiographs are used to diagnose many conditions involving the chest wall, including its bones, and also structures contained within the thoracic cavity including the lungs, heart, and great vessels. Pneumonia and congestive heart failure are very commonly diagnosed by chest radiograph. Chest radiographs are also used to screen for job-related lung disease in industries such as mining where workers are exposed to dust. For some conditions of the chest, radiography is good for screening but poor for diagnosis. When a condition is suspected based on chest radiography, additional imaging of the chest can be obtained to definitively diagnose the condition or to provide evidence in favor of the diagnosis suggested by initial chest radiography. Unless a fractured rib is suspected of being displaced, and therefore likely to cause damage to the lungs and other tissue structures, x-ray of the chest is not necessary as it will not alter patient management. The main regions where a chest X-ray may identify problems may be summarized as ABCDEF by their first letters: Airways, including hilar adenopathy or enlargement Breast shadows Bones, e.g.

Deep learning parametric response mapping from inspiratory chest CT scans: a new approach for small airway disease screening

Jiancheng Yang, Zhiye Wang, Jun Lu, Zhigang Li, Lin Qi, Ming Li, Bo Du, Yuxuan Sun, Ziyi Liu

Objectives Parametric response mapping (PRM) enables the evaluation of small airway disease (SAD) at the voxel level, but requires both inspiratory and expiratory chest CT scans. We hypothesize that deep learning PRM from inspiratory chest CT scans can eff ...

London2023

GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification

Deep learning parametric response mapping from inspiratory chest CT scans: a new approach for small airway disease screening

Class Specific Feature Disentanglement and Text Embeddings for Multi-label Generalized Zero Shot CXR Classification

Class Specific Feature Disentanglement and Text Embeddings for Multi-label Generalized Zero Shot CXR Classification

GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification

Deep learning parametric response mapping from inspiratory chest CT scans: a new approach for small airway disease screening