Inceptionism and Residualism in the Classification of Breast Fine-Needle Aspiration Cytology Cell Samples

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Amartya Ranjan Saikia

Fine needle aspiration cytology (FNAC) entails using a narrow gauge needle to collect a sample of a lesion for microscopic examination. It allows a minimally invasive, rapid diagnosis of tissue but does not preserve its histological architecture. This project presents a comparison of the various fine-tuned transfer learned classification approaches based on deep convolutional neural networks (CNN) for diagnosing the cell samples.

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