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- W3090256880 abstract "Automatic classification algorithms are an important component of expert decision support systems that are used in a number of medical applications including diagnostic radiology and disease detection. This study proposes a deep learning-based framework for medical image classification using wavelet features. Convolutional neural networks are incorporated to discover informative latent patterns and features from a set of X-ray images pertaining to human body parts. The features are then passed to a classifier for labelling the respective X-ray images. The experimental results show that the low-pass filter wavelet-based convolutional model outperforms the original convolutional network and some models for classifying X-ray images. The performance of the proposed method implies that it can be implemented effectively in practice for disease detection using radiological images." @default.
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- W3090256880 date "2020-07-01" @default.
- W3090256880 modified "2023-10-06" @default.
- W3090256880 title "Convolutional Neural Network for Medical Image Classification using Wavelet Features" @default.
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- W3090256880 doi "https://doi.org/10.1109/ijcnn48605.2020.9206791" @default.
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