ICA separation of functional components from dynamic cardiac PET data

被引：1
|
作者：
Magadán-Méndez, M [1 ]
Kivimäki, A [1 ]
Ruotsalainen, U [1 ]
机构：
[1] Tampere Univ Technol, Inst Signal Proc, Tampere Grad Sch Informat Sci, FIN-33101 Tampere, Finland
来源：
2003 IEEE NUCLEAR SCIENCE SYMPOSIUM, CONFERENCE RECORD, VOLS 1-5 | 2004年
关键词：
image segmentation; noise separation; numerical phantom; PET heart data;
D O I：
10.1109/NSSMIC.2003.1352426
中图分类号：
TL [原子能技术]; O571 [原子核物理学];
学科分类号：
0827 ; 082701 ;
摘要：
The aim of this study was to improve detection of different heart tissues, and specially their boundaries, in (H2O)-O-15 PET (Positron Emission Tomography) heart images. This problem was considered as a Blind Source Separation problem. In order to solve it we applied ICA (Independent Component Analysis) on dynamic image data and measured projection profiles (sinograms). The testing was based on two kinds of data: a simple dynamic numerical phantom and human heart data acquired during resting state. The sensitivity of ICA to noise was examined on phantom data, where ICA seemed to be less sensitive to noise on sinogram data than on image data. On cardiac rest data, the results were in line with the results on phantom data.
引用
收藏
页码：2618 / 2622
页数：5
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