… chest radiography, advanced lung imaging modalities, for … with the progress of image
analysis techniques provide the … as chronic obstructive lung disease, interstitial lung disease, …

… of deep learning algorithms in lung cancer diagnosis and prognosis. … in lung cancer patient
care. We point out some promising future directions for lung cancer pathology image analysis…

… images to derive sets of numeric quantities that measure heterogeneity. Studies on lung
cancer have shown that texture analysis … on texture analysis in lung cancer imaging. We also …

… and analysis of shape and appearance of the detected lung nodules. Dealing with all aspects
of image analysis of the data, this book examines: Lung … Lung registration Detection of lung …

… A strong correlation between quantitative LUS grayscale analysis and EVLW density in
isolated bovine lungs (40). This could improve early diagnosis of ARDS, potentially promoting a …

… analysis of the lung parenchyma derives from the knowledge that the generic term “ILD”
includes multiple different diseases with numerous different imaging … for surgical lung biopsy …

… lung disease patterns in COVID-19. The overarching goal of this systematic review and
meta-analysis is to … thus far describing COVID-19 lung imaging data in the pediatric population. …

… lung segmentation, which greatly limits the use of image … methods for lung segmentation on
CT images is provided, … the most common lung abnormalities observed on CT images. In an …

… Automating the analysis of such data is, therefore, a necessity and this has created a rapidly
… imaging. This paper presents a review of the literature on computer analysis of the lungs in …

… image analysis for lung cancer owing to the complexity and heterogeneity of the disease. In
this study, we developed a pathological image analysis … with lung cancer. The pathological …