Deep Learning Using Havrda-Charvat Entropy for Classification of Pulmonary Optical Endomicroscopy
Abstract
Pulmonary optical endomicroscopy (POE) is an imaging technology in real time. It allows to examine pulmonary alveoli at a microscopic level. Acquired in clinical settings, a POE image sequence can have as much as 25% of the sequence being uninformative frames (i.e. pure-noise and motion artifacts). For future data analysis, these uninformative frames must be first removed from the sequence. Therefore, the objective of our work is to develop an...
Paper Details
Title
Deep Learning Using Havrda-Charvat Entropy for Classification of Pulmonary Optical Endomicroscopy
Published Date
Dec 1, 2021
Journal
Volume
42
Issue
6
Pages
400 - 406
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