Abstract
We present a Multiscale Convolutional Neural Network (MCNN) approach for vision–based classification of cells. Based on several deep Convolutional Neural Networks (CNN) acting at different resolutions, the proposed architecture avoid the classical handcrafted features extraction step, by processing features extraction and classification as a whole. The proposed approach gives better classification rates than classical state–of–the–art methods allowing a safer Computer–Aided Diagnosis of pleural cancer.
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Buyssens, P., Elmoataz, A., Lézoray, O. (2013). Multiscale Convolutional Neural Networks for Vision–Based Classification of Cells. In: Lee, K.M., Matsushita, Y., Rehg, J.M., Hu, Z. (eds) Computer Vision – ACCV 2012. ACCV 2012. Lecture Notes in Computer Science, vol 7725. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37444-9_27
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DOI: https://doi.org/10.1007/978-3-642-37444-9_27
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