Chest X-ray Image Processing: Clipped Anatomy Detection and Cardiothoracic Ratio Estimation

The cardiothoracic ratio (CTR) is a clinical criteria used to estimate heart size and possible linked abnormality, such as cardiomegaly, from chest X-ray (CXR) images. Visual evaluation of CTR in clinical practice is time-consuming and may introduce variation across interpreters. Obtaining the objective measurement of CTR in an automatic way will decrease the subjectivity of the radiologist’s evaluation and will give more support to their diagnosis during follow-up examinations. The goal of this thesis was to investigate the automatic measurement of the CTR. Two segmentation-based approaches have been proposed for the calculation of the CTR from CXR images. A first method estimates the CTR based only on lung segmentation, and a second method adds the segmentation of the heart for the estimation of the CTR. These methods were also developed to be robust to the presence of clipped lung on the image, which is one of the quality checks that should be observed before each CXR analysis. The calculation of the CTR from only lung segmentation obtains better results in this thesis when compared to the CTR calculation from both lung and heart segmentations. It shows a mean and a standard deviation of the absolute error of 0.038±0.040 when tested on non-clipped CXRs and 0.058±0.057 when tested on CXRs with clipped lungs. Based on this lung segmentation model, an algorithm to detect the presence of clipped anatomy is proposed, showing promising results. Thanks to the possibility to quickly apply the automatic CTR calculation to a large number of CXRs, a short population study was carried out on 25,369 CXRs from the CheXpert dataset. It allows to study how presumably normal CTR values change due to age and gender. An increase in mean CTR from 0.448 to 0.562 from 18-years-old to 90-years-old patients has been reported, with a higher increase for female than male.