TITLE:
A Comparative Study of Automated Segmentation Methods for Use in a Microwave Tomography System for Imaging Intracerebral Hemorrhage in Stroke Patients
AUTHORS:
Qaiser Mahmood, Shaochuan Li, Andreas Fhager, Stefan Candefjord, Artur Chodorowski, Andrew Mehnert, Mikael Persson
KEYWORDS:
Magnetic Resonance Imaging, Automatic Segmentation, Microwave, Dielectric Head Model, Intracerebral Hemorrhage Reconstruction
JOURNAL NAME:
Journal of Electromagnetic Analysis and Applications,
Vol.7 No.5,
May
19,
2015
ABSTRACT: Microwave technology offers the possibility
for pre-hospital stroke detection as we have previously demonstrated using
non-imaging diagnostics. The focus in this paper is on image-based diagnostics
wherein the technical and computational complexities of image reconstruction
are a challenge for clinical realization. Herein we investigate whether
information about a patient’s brain anatomy obtained prior to a stroke event
can be used to facilitate image-based stroke diagnostics. A priori information
can be obtained by segmenting the patient’s head tissues from magnetic
resonance images. Expert manual segmentation is presently the gold standard,
but it is laborious and subjective. A fully automatic method is thus desirable.
This paper presents an evaluation of several such methods using both synthetic
magnetic resonance imaging (MRI) data and real data from four healthy subjects.
The segmentation was performed on the full 3D MRI data, whereas the
electromagnetic evaluation was performed using a 2D slice. The methods were
evaluated in terms of: i) tissue classification accuracy over all tissues with
respect to ground truth, ii) the accuracy of the simulated electromagnetic wave
propagation through the head, and iii) the accuracy of the image reconstruction
of the hemorrhage. The segmentation accuracy was measured in terms of the
degree of overlap (Dice score) with the ground truth. The electromagnetic
simulation accuracy was measured in terms of signal deviation relative to the
simulation based on the ground truth. Finally, the image reconstruction
accuracy was measured in terms of the Dice score, relative error of dielectric
properties, and visual comparison between the true and reconstructed
intracerebral hemorrhage. The results show that accurate segmentation of
tissues (Dice score = 0.97) from the MRI data can lead to accurate image
reconstruction (relative error = 0.24) for the intracerebral hemorrhage in the
subject’s brain. They also suggest that accurate automated segmentation can be
used as a surrogate for manual segmentation and can facilitate the rapid
diagnosis of intracerebral hemorrhage in stroke patients using a microwave
imaging system.