Abstract:

BACKGROUND: Chest X-ray film is one of important means for diagnosing lung and chest diseases in a clinic, however, large amounts of data processing work bring tremendous pressure.
OBJECTIVE: To verify the feasibility of evaluating lung and chest physiological condition with principal component analysis (PCA), proposing the concept of establishing physical health chest lung model during clinical practice.
METHODS: Chest X-ray films were collected from 202 healthy adults. Nine experimental projects of each chest were measured with the help of the software MxLiteView. We realized the PCA algorithm and processed the experimental data based on MATLAB.
RESULTS AND CONCLUSION: Principal component variables were obtained by data processing, which can represent physical health of a specific lung and chest region by analysis and evaluation. It is demonstrated that the PCA can be fast and effective in pre-processing and analyzing a large number of X-ray chest physiological data, directly reflect the physical health condition of human lung and chest. The results further confirm the feasibility of establishing lung health screening model. In clinical practice, it will help alleviate the waste of human resources.