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Sparse shape representation using the Laplace-Beltrami eigenfunctions and its application to modeling subcortical structures.

, , , , and . MMBIA, page 25-32. IEEE, (2012)

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Agreement between the white matter connectivity based on the tensor-based morphometry and the volumetric white matter parcellations based on diffusion tensor imaging., , , , , , , and . ISBI, page 42-45. IEEE, (2012)2.4 ATOMUS: A 5nm 32TFLOPS/128TOPS ML System-on-Chip for Latency Critical Applications., , , , , , , , , and 56 other author(s). ISSCC, page 42-44. IEEE, (2024)Sparse shape representation using the Laplace-Beltrami eigenfunctions and its application to modeling subcortical structures., , , , and . MMBIA, page 25-32. IEEE, (2012)Heat Kernel Smoothing via Laplace-Beltrami Eigenfunctions and Its Application to Subcortical Structure Modeling., , , , , and . PSIVT (1), volume 7087 of Lecture Notes in Computer Science, page 36-47. Springer, (2011)Improved statistical power with a sparse shape model in detecting an aging effect in the hippocampus and amygdala., , , , , , and . Medical Imaging: Image Processing, volume 9034 of SPIE Proceedings, page 90340Y. SPIE, (2014)Structural connectivity via the tensor-based morphometry., , , , , , and . ISBI, page 808-811. IEEE, (2011)Group-wise analysis on myelination profiles of cerebral cortex using the second eigenvector of Laplace-Beltrami operator., , , , and . ISBI, page 1007-1010. IEEE, (2014)