Chung et al. 2024 is presented in OHBM 2024.
The method and codes are published in
Chen, Z., Das, S., Chung, M.K. 2023, Sulcal Pattern Matching with the Wasserstein Distance, International Symposium in Biomedcial Imaging (ISBI). Poster version. The following script will perform the basic sulcal pattern matching.
SCRIPT1_dataPreprocess.m prepares data and performs heat kernel smoothing (Sections 2.1 and 2.2)
SCRIPT2_registration.m performs the Wasserstein disatnce based sulcal pattern matching (Sections 2.3 and 2.4)
SCRIPT3_validation.m performs the Validation against the Hungarian Algorithm (Section 3.1)
(C) 2022- Zijian Chen, Moo K. Chung University of Wisconsin-Madison
SCRIPT.m generating sulcal tree patterns below published in
Huang, S.-G., Lyu, I., Qiu, A., Chung, M.K. 2020. Fast polynomial approximation of heat kernel convolution on manifolds and its application to brain sulcal and gyral graph pattern analysis, IEEE Transactions on Medical Imaging 39:2201-2212 https://pages.stat.wisc.edu/~mchung/papers/huang.2020.TMI.pdf
We can perform the heat kernel smoothing using SPHARM based on
Chung, M.K., Dalton, K.M., Shen, L., L., Evans, A.C., Davidson, R.J. 2007. Weighted Fourier series representation and its application to quantifying the amount of gray matter. Special Issue of IEEE Transactions on Medical Imaging 26:566-581.
See https://pages.stat.wisc.edu/~mchung/softwares/weighted-SPHARM/weighted-SPHARM.html for additional codes. The method can resample mesh sizes and reduce the data size further.
(C) 2022- Moo K. Chung University of Wisconsin-Madison