.png){kind=icon}
返回
Feature-Based Deformable Registration Using Minimal Spanning Tree for Prostate MR Segmentation
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2019.2943485.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Automatic and accurate segmentation of the prostate is still a challenging task due to intensity inhomogeneity and complicated deformation of MR images. To tackle these problems with multi-atlas segmentation, in this paper, we propose a new metric for image registration and new descriptor for label fusion. First, to reduce the amount of edges in entropic graph, a modified ff-mutual information (alpha-MI) based on fast minimal spanning tree (MST) is implemented for deformable registration. Second, localized alpha-MI allowing for the spatial information is proposed with the stochastic gradient optimization, and the feature space is encoded by a sparse auto-encoder. Finally, a multi-scale descriptor utilizing local self-similarity is integrated into the patch-based label fusion to obtain final segmentation. Experiments were performed on two subsets of totally 46 T2-weighted prostate MR images from 46 patients. Compared to alpha-MI based on k-nearest neighbor graph, the registration time of alpha-MI based on fast MST can be reduced by almost half. The median Dice overlap of registration using localized alpha-MI on one subset is shown to improve significantly from 0.725 to 0.764 (p = 1:14 x 10(-5)), compared to using alpha-MI without the spatial information. The median Dice overlap of prostate segmentation using the proposed method on 20 testing images of another subset is 0.871, and the median Hausdorff distance is 8.013 mm, which demonstrate a comparable accuracy to state-of-the-art methods.
Keyword:
Deformable registration
alpha-mutual information
minimal spanning tree
prostate segmentation
patch-based label fusion
local self-similarity
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
The influence of various precursors on solar-light-driven g-C3N4 synthesis and its effect on photocatalytic tetracycline hydrochloride (TCH) degradation各种前体对太阳光驱动的g-C3N4合成及其对光催化盐酸四环素 (TCH) 降解的影响
PREAI
分享收藏Atlas registration and ensemble deep convolutional neural network-based prostate segmentation using magnetic resonance imaging.png)
NEUROCOMPUTING
NEUROCOMPUTINGIF6.5
PREAI
分享收藏
MIND: Modality independent neighbourhood descriptor for multi-modal deformable registrationMEDICAL IMAGE ANALYSIS
MEDICAL IMAGE ANALYSISIF11.8
PREAI
分享收藏Deformable segmentation via sparse representation and dictionary learning基于稀疏表示和字典学习的可变形图像分割MEDICAL IMAGE ANALYSIS
MEDICAL IMAGE ANALYSISIF11.8
PREAI
分享收藏
查看更多内容