68 citations · 84 across the 6 of their papers we have counts for
6 papers
FreeCOS: Self-Supervised Learning from Fractals and Unlabeled Images for Curvilinear Object Segmentation
Tianyi Shi, Xiaohuan Ding, Liang Zhang +1
Curvilinear object segmentation is critical for many applications. However, manually annotating curvilinear objects is very time-consuming and error-prone, yielding insufficiently…
Affinity Feature Strengthening for Accurate, Complete and Robust Vessel Segmentation
Tianyi Shi, Xiaohuan Ding, Wei Zhou +4
Vessel segmentation is crucial in many medical image applications, such as detecting coronary stenoses, retinal vessel diseases and brain aneurysms. However, achieving high pixel-w…
Learning Green's functions associated with time-dependent partial differential equations
Nicolas Boullé, Seick Kim, Tianyi Shi +1
Neural operators are a popular technique in scientific machine learning to learn a mathematical model of the behavior of unknown physical systems from data. Neural operators are es…
Local Intensity Order Transformation for Robust Curvilinear Object Segmentation
Tianyi Shi, Nicolas Boutry, Yongchao Xu +1
Segmentation of curvilinear structures is important in many applications, such as retinal blood vessel segmentation for early detection of vessel diseases and pavement crack segmen…
Parallel algorithms for computing the tensor-train decomposition
Tianyi Shi, Maximilian Ruth, Alex Townsend
The tensor-train (TT) decomposition expresses a tensor in a data-sparse format used in molecular simulations, high-order correlation functions, and optimization. In this paper, we…
On the compressibility of tensors
Tianyi Shi, Alex Townsend
Tensors are often compressed by expressing them in low rank tensor formats. In this paper, we develop three methodologies that bound the compressibility of a tensor: (1) Algebraic…