Fourier transform of percoll gradients boosts cnn classification of hereditary hemolytic anemias

Sadafi A, Moya Sans LM, Makhro A, Livshits L, Navab N, Bogdanova A, Albarqouni S, Marr C (2021)


Publication Type: Conference contribution

Publication year: 2021

Journal

Publisher: IEEE Computer Society

Book Volume: 2021-April

Pages Range: 966-970

Conference Proceedings Title: Proceedings - International Symposium on Biomedical Imaging

Event location: Nice, FRA

ISBN: 9781665412469

DOI: 10.1109/ISBI48211.2021.9433788

Abstract

Hereditary hemolytic anemias are genetic disorders that affect the shape and density of red blood cells. Genetic tests currently used to diagnose such anemias are expensive and unavailable in the majority of clinical labs. Here, we propose a method for identifying hereditary hemolytic anemias based on a standard biochemistry method, called Percoll gradient, obtained by centrifuging a patient's blood. Our hybrid approach consists on using spatial data-driven features, extracted with a convolutional neural network and spectral handcrafted features obtained from fast Fourier transform. We compare late and early feature fusion with AlexNet and VGG16 architectures. AlexNet with late fusion of spectral features performs better compared to other approaches. We achieved an average F1-score of 88% on different classes suggesting the possibility of diagnosing of hereditary hemolytic anemias from Percoll gradients. Finally, we utilize Grad-CAM to explore the spatial features used for classification.

Involved external institutions

How to cite

APA:

Sadafi, A., Moya Sans, L.M., Makhro, A., Livshits, L., Navab, N., Bogdanova, A.,... Marr, C. (2021). Fourier transform of percoll gradients boosts cnn classification of hereditary hemolytic anemias. In Proceedings - International Symposium on Biomedical Imaging (pp. 966-970). Nice, FRA: IEEE Computer Society.

MLA:

Sadafi, Ario, et al. "Fourier transform of percoll gradients boosts cnn classification of hereditary hemolytic anemias." Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, ISBI 2021, Nice, FRA IEEE Computer Society, 2021. 966-970.

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