@inproceedings{677b2f9d9063428d904ecd61d9fc3fa1,
title = "Similarity-based appearance-prior for fitting a subdivision mesh in gene expression images",
abstract = "Automated segmentation of multi-part anatomical objects in images is a challenging task. In this paper, we propose a similarity-based appearance-prior to fit a compartmental geometric atlas of the mouse brain in gene expression images. A subdivision mesh which is used to model the geometry is deformed using a Markov Random Field (MRF) framework. The proposed appearance-prior is computed as a function of the similarity between local patches at corresponding atlas locations from two images. In addition, we introduce a similarity-saliency score to select the mesh points that are relevant for the computation of the proposed prior. Our method significantly improves the accuracy of the atlas fitting, especially in the regions that are influenced by the selected similarity-salient points, and outperforms the previous subdivision mesh fitting methods for gene expression images.",
keywords = "Gene expression image, Segmentation, Subdivision mesh",
author = "Le, {Yen H.} and Uday Kurkure and Nikos Paragios and Tao Ju and Carson, {James P.} and Kakadiaris, {Ioannis A.}",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2012.; 15th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2012 ; Conference date: 01-10-2012 Through 05-10-2012",
year = "2012",
doi = "10.1007/978-3-642-33415-3_71",
language = "English",
isbn = "9783642334146",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "577--584",
editor = "Nicholas Ayache and Herve Delingette and Polina Golland and Kensaku Mori",
booktitle = "Medical Image Computing and Computer-Assisted Intervention, MICCAI2012 - 15th International Conference, Proceedings",
}