Texture Classification Network Integrating Adaptive Wavelet Transform

arXiv:2404.05300v1 Announce Type: new
Abstract: Graves' disease is a common condition that is diagnosed clinically by determining the smoothness of the thyroid texture and its morphology in ultrasound images. Currently, the most widely used approach for the automated diagnosis of Graves' disease utilizes Convolutional Neural Networks (CNNs) for both feature extraction and classification. However, these methods demonstrate limited efficacy in capturing texture features. Given the high capacity of wavelets in describing texture features, this research integrates learnable wavelet modules utilizing …

abstract arxiv automated classification cnns convolutional neural networks cs.cv diagnosis disease extraction feature feature extraction images network networks neural networks texture type wavelet