تقرير
Deep learning based prediction of Alzheimer's disease from magnetic resonance images
| العنوان: | Deep learning based prediction of Alzheimer's disease from magnetic resonance images |
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| المؤلفون: | Subramoniam, Manu, R., Aparna T., R., Anurenjan P., G, Sreeni K. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Electrical Engineering and Systems Science - Image and Video Processing, Electrical Engineering and Systems Science - Signal Processing |
| الوصف: | Alzheimer's disease (AD) is an irreversible, progressive neuro degenerative disorder that slowly destroys memory and thinking skills and eventually, the ability to carry out the simplest tasks. In this paper, a deep neural network based prediction of AD from magnetic resonance images (MRI) is proposed. The state of the art image classification networks like VGG, residual networks (ResNet) etc. with transfer learning shows promising results. Performance of pre-trained versions of these networks are improved by transfer learning. ResNet based architecture with large number of layers is found to give the best result in terms of predicting different stages of the disease. The experiments are conducted on Kaggle dataset. Comment: Some errors in the results section, which has to be corrected |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2101.04961 |
| رقم الأكسشن: | edsarx.2101.04961 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |