Multi-Scale Anisotropic Fourth-Order Diffusion Improves Ridge and Valley Localization
This work addresses vessel detection in medical imaging, offering an incremental improvement over existing methods.
The authors tackled the problem of improving ridge and valley localization in noisy images with multi-scale vessels by proposing a novel multi-scale anisotropic fourth-order diffusion filter, which better restores centerlines compared to previous filters.
Ridge and valley enhancing filters are widely used in applications such as vessel detection in medical image computing. When images are degraded by noise or include vessels at different scales, such filters are an essential step for meaningful and stable vessel localization. In this work, we propose a novel multi-scale anisotropic fourth-order diffusion equation that allows us to smooth along vessels, while sharpening them in the orthogonal direction. The proposed filter uses a fourth order diffusion tensor whose eigentensors and eigenvalues are determined from the local Hessian matrix, at a scale that is automatically selected for each pixel. We discuss efficient implementation using a Fast Explicit Diffusion scheme and demonstrate results on synthetic images and vessels in fundus images. Compared to previous isotropic and anisotropic fourth-order filters, as well as established second-order vessel enhancing filters, our newly proposed one better restores the centerlines in all cases.