SurfCut: Surfaces of Minimal Paths From Topological Structures
This addresses a domain-specific problem in 3D image processing for applications like medical imaging or computer vision, presenting a novel method rather than an incremental improvement.
The paper tackles the problem of extracting smooth surfaces with unknown 3D curve boundaries from noisy 3D images using a seed point, achieving higher accuracy and lower computational cost than state-of-the-art methods in experiments on three datasets.
We present SurfCut, an algorithm for extracting a smooth, simple surface with an unknown 3D curve boundary from a noisy 3D image and a seed point. Our method is built on the novel observation that certain ridge curves of a function defined on a front propagated using the Fast Marching algorithm lie on the surface. Our method extracts and cuts these ridges to form the surface boundary. Our surface extraction algorithm is built on the novel observation that the surface lies in a valley of the distance from Fast Marching. We show that the resulting surface is a collection of minimal paths. Using the framework of cubical complexes and Morse theory, we design algorithms to extract these critical structures robustly. Experiments on three 3D datasets show the robustness of our method, and that it achieves higher accuracy with lower computational cost than state-of-the-art.