Classification of Microwave Scattering Data based on a Subspace Distance with Application to Detection of Bleeding Stroke
Paper i proceeding, 2009

This paper demonstrates the usefulness of a classifier based on a subspace distance for the detection of bleeding stroke based on microwave scattering measurements from an antenna array placed around the skull. This discriminating classifier is suitable for high dimensional data applications when the number of training data samples is less than the data dimension. The proposed classifier was tested on both clinical and experimental data to separate bleeding subjects from non-bleeding ones. A pseudo-inverse Mahalanobis distance based classifier and a classifier based on the Euclidean distance were used on clinical data for the purpose of comparison with the proposed classifier.

Författare

Mohammad Ali Khorshidi

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

Tomas McKelvey

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

Mikael Persson

Bioeffekter

Hana Dobsicek Trefna

Bioeffekter

2009 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2009; Aruba; Netherlands; 13 December 2009 through 16 December 2009

301-304

Ämneskategorier

Signalbehandling

DOI

10.1109/CAMSAP.2009.5413272

ISBN

978-142445180-7

Mer information

Skapat

2017-10-08