Developing learnable wavelet methods for medical imaging
My research focuses on learnable wavelets — adaptive signal decomposition where filter coefficients are optimized during training. This bridges classical wavelet theory with deep learning for medical imaging applications like tumor detection, CT reconstruction, and radiomics.