Abstract
Among various medical imaging tools, chest radiographs are the most important and widely used diagnostic tool for detection of thoracic pathologies. Researches are being carried out in order to propose robust automatic diagnostic tool for detection of pathologies from chest radiographs. Artificial Intelligence techniques especially deep learning methodologies have been found to be giving promising results in automating the field of medicine. Lot of research has been done for automatic and fast detection of pneumothorax from chest radiographs while proposing several frameworks based on artificial intelligence and machine learning techniques. This study summarizes the existing literature for the automatic detection of pneumothorax from chest x-rays along with describing the available chest radiographs datasets. The comparative analysis of the literature is also provided in terms of goodness and limitations of the existing literature along with highlighting the research gaps which need to be further explored. The paper provides a brief overview of the present work for pneumothorax detection for helping the researchers in selection of optimal approach for future research.
Abstract (translated)
URL
https://arxiv.org/abs/2012.11214
