Scalable Biologically-Aware Skeleton Generation for Connectomic Volumes-Reference-Cited by-同舟云学术

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Scalable Biologically-Aware Skeleton Generation for Connectomic Volumes

Published:2022-09 Issue:9 Volume:41 Page:2360-2370
ISSN:0278-0062
Container-title:IEEE Transactions on Medical Imaging
language:
Short-container-title:IEEE Trans. Med. Imaging

Author:

Matejek Brian¹^ORCID,Franzmeyer Tim²,Wei Donglai¹,Wang Xueying³^ORCID,Zhao Jinglin³,Palagyi Kalman⁴^ORCID,Lichtman Jeff W.³,Pfister Hanspeter¹^ORCID

Affiliation:

1. School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA

2. Department of Mechanical and Process Engineering, ETH Zurich, Zurich, Switzerland

3. Department of Molecular and Cellular Biology, Center for Brain Science, Harvard University, Cambridge, MA, USA

4. Department of Image Processing and Computer Graphics, University of Szeged, Szeged, Hungary

Funder

NSF

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Science Applications,Radiological and Ultrasound Technology,Software

Link

https://ieeexplore.ieee.org/ielam/42/9872156/9748108-aam.pdf

Reference49 articles.

1. A deep structured learning approach towards automating connectome reconstruction from 3D electron micrographs;funke;arXiv 1709 02974,2017

2. A topology-preserving parallel 3D thinning algorithm for extracting the curve skeleton

3. A New Fuzzy Skeletonization Algorithm and Its Applications to Medical Imaging

4. Generation of a Graph Representation from Three-Dimensional Skeletons of the Liver Vasculature

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