From Event: SPIE Medical Imaging, 2023
Measuring hyperplasia in Atlantic salmon gills can give important insight into fish health and environmental conditions such as water quality. This paper proposes a novel histology image classification technique to identify hyperplastic regions using an emerging signal decomposition technique, Empirical Wavelet Transform (EWT) in combination with a fully connected neural network (FCNN). Due to its adaptive nature, we hypothesise and show that EWT effectively represents unique features of gill histopathology whole slide images that help in the classification task. Our hybrid approach is unique and significantly outperformed regular deep learning-based methods considering a joint speed-accuracy metric.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alexander F. B. Carmichael, Johanna L. Baily, Aaron Reeves, Gabriela Ochoa, Annette S. Boerlage, George Gunn, Rosa Allshire, and Deepayan Bhowmik, "Analysing hyperplasia in Atlantic salmon gills using empirical wavelets," Proc. SPIE 12471, Medical Imaging 2023: Digital and Computational Pathology, 124710I (Presented at SPIE Medical Imaging: February 21, 2023; Published: 6 April 2023); https://doi.org/10.1117/12.2655889.