In this study, ten
different types of cancer were classified with deep convolutional neural
networks (DCNN). A total of 10,000 MRI (Magnetic Resonance Imaging) data were
used for ten cancer patients, including 1000 MRI data for each cancer type.
Although the images were reduced to 28x28 pixels, the DCNN model performed
classification with an accuracy rate of 0.98 after 27 seconds and 15 epochs of
training. The error rate in the last epoch in the study is also very close to
zero. A highly successful classification has been achieved with the proposed
DCNN model.
Deep Convolutional Neural Network Cancer Types Classification Accuracy
Birincil Dil | İngilizce |
---|---|
Bölüm | Araştırma Makalesi |
Yazarlar | |
Yayımlanma Tarihi | 1 Nisan 2018 |
Yayımlandığı Sayı | Yıl 2018 Cilt: 6 |
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