Effects of Registration Regularization and Atlas Sharpness on Segmentation Accuracy 1st Edition by BT Thomas Yeo, Mert R Sabuncu, Rahul Desikan, Bruce Fischl, Polina Golland ISBN 9783540757573

Effects of Registration Regularization and Atlas Sharpness on Segmentation Accuracy 1st Edition by BT Thomas Yeo, Mert R Sabuncu, Rahul Desikan, Bruce Fischl, Polina Golland – Ebook PDF Instant Download/Delivery. 9783540757573
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ISBN 13: 9783540757573
Author: BT Thomas Yeo, Mert R Sabuncu, Rahul Desikan, Bruce Fischl, Polina Golland

In this paper, we propose a unified framework for computing atlases from manually labeled data at various degrees of “sharpness” and the joint registration-segmentation of a new brain with these atlases. In non-rigid registration, the tradeoff between warp regularization and image fidelity is typically set empirically. In segmentation, this leads to a probabilistic atlas of arbitrary “sharpness”: weak regularization results in well-aligned training images and a “sharp” atlas; strong regularization yields a “blurry” atlas. We study the effects of this tradeoff in the context of cortical surface parcellation by comparing three special cases of our framework, namely: progressive registration-segmentation of a new brain to increasingly “sharp” atlases with increasingly flexible warps; secondly, progressive registration to a single atlas with increasingly flexible warps; and thirdly, registration to a single atlas with fixed constrained warps. The optimal parcellation in all three cases corresponds to a unique balance of atlas “sharpness” and warp regularization that yield statistically significant improvements over the previously demonstrated parcellation results.

Effects of Registration Regularization and Atlas Sharpness on Segmentation Accuracy 1st Table of contents:

1 Introduction
2 Theory
2.1 Generative Model for Registration and Segmentation
2.2 Atlas Building: Estimating Parameters of Generative Model
2.3 Registration and Segmentation of a New Image
3 Cortical Surface Parcellation
3.1 Generative Model for Registration and Segmentation
3.2 Atlas Building: Estimating Parameters of Generative Model
3.3 Registration and Segmentation of a New Image
4 Experiments and Discussion
4.1 Exploration of Smoothness S and Atlas Aα
4.2 Comparison with FreeSurfer

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