Dynamic chest image analysis: evaluation of model-based ventilation study with pyramid images

The aim of the study "dynamic chest image analysis" is to develop computer analysis and visualization methods for showing focal and general abnormalities of lung ventilation and perfusion based on a sequence of digital chest fluoroscopy frames collected at different phases of the respiratory/cardiac cycles in a short period of time. A multiresolutional method for ventilation study with an explicit ventilation model based on pyramid images is proposed. The model aims at extracting accurate, geographic ventilation parameters, and the pyramid helps in understanding ventilation at multiple resolutions and speeding up the convergence process in optimization. A research prototype has been produced in MATLAB. Both artificial signals and clinical cases are used for the evaluation. For artificial signals, the authors use the true parameters as reference for quantitative examination of the result accuracy. For clinical cases (including 53 patients), they visually divide the lung field into several regions (apex; upper, mid, lower fields; lateral; and base), classify the regional, functional abnormalities into five types (no ventilation, reduced ventilation, asynchronous ventilation, non-symmetrical ventilation and compensatory ventilation) and use high resolution computed tomography (HRCT) as reference to examine the correlation between structural abnormalities and functional abnormalities. They have found that asynchronous ventilation and non-symmetrical ventilation are the most frequent functional abnormalities.