@inproceedings{3561b4ebdff045db8ae8854a90c5bdd4,
title = "Diverse multiple prediction on neuron image reconstruction",
abstract = "Neuron reconstruction from anisotropic 3D Electron Microscopy (EM) images is a challenging problem. One often considers an input image as a stack of 2D image slices, and consider both intra and inter slice segments information. In this paper, we present a new segmentation algorithm which builds a unified energy function and jointly optimize the per-slice segmentation and the inter-slice consistency. To find an optimal solution from the huge solution space, we propose a novel diverse multiple prediction method which also encourages diversity in partial solutions. We demonstrate the strength of our method in several public datasets.",
author = "Ze Ye and Cong Chen and Changhe Yuan and Chao Chen",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019 ; Conference date: 13-10-2019 Through 17-10-2019",
year = "2019",
doi = "10.1007/978-3-030-32239-7\_51",
language = "English",
isbn = "9783030322380",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "460--468",
editor = "Dinggang Shen and Pew-Thian Yap and Tianming Liu and Peters, \{Terry M.\} and Ali Khan and Staib, \{Lawrence H.\} and Caroline Essert and Sean Zhou",
booktitle = "Medical Image Computing and Computer Assisted Intervention – MICCAI 2019 - 22nd International Conference, Proceedings",
}