Spectral Data Augmentation Techniques to quantify Lung Pathology from CT-images
ISBI, pp. 586-590, 2020.
Data augmentation is of paramount importance in biomedical image processing tasks, characterized by inadequate amounts of labelled data, to best use all of the data that is present. In-use techniques range from intensity transformations and elastic deformations, to linearly combining existing data points to make new ones. In this work, ...More
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