Incremental activation detection in FMRI series using Kalman filtering

被引：0

作者：

Roche, A ^{[1
]}

Lahaye, PJ ^{[1
]}

Poline, JB ^{[1
]}

机构：

[1] CEA, Serv Hosp Frederic Joliot, F-91406 Orsay, France

来源：

2004 2ND IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: MACRO TO NANO, VOLS 1 AND 2 | 2004年

关键词：

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

We propose a new detection algorithm for functional magnetic resonance imaging (fMRI) data. Our basic idea is to use an extended Kalman filter (EKF) to fit a general linear model on fMRI time courses, under the assumption of one-degree autoregressive noise with unknown autocorrelation. Because the EKF is designed to be an incremental algorithm, it enables us to compute activation maps on each scan time, and this at moderate computational cost. While our technique is evaluated "offline" in this paper, we believe it is potentially well-suited for future real-time applications.

引用

页码：376 / 379

页数：4

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