Ischemic stroke enhancement using a variational model and the expectation maximization method
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In order to enable less experienced physicians to reliably detect early signs of stroke, A novel approach was proposed to enhance the visual perception of ischemic stroke in non-enhanced CT.
A set of 39 retrospective CT scans were used, divided into 23 cases of acute ischemic stroke and 16 normal patients. Stroke cases were obtained within 4.5 h of symptom onset and with a mean NIHSS of 12.9±7.4. After selection of adjunct slices from the CT exam, image averaging was performed to reduce the noise and redundant information. This was followed by a variational decomposition model to keep the relevant component of the image. The expectation maximization method was applied to generate enhanced images.
We determined a test to evaluate the performance of observers in a clinical environment with and without the aid of enhanced images. The overall sensitivity of the observer’s analysis was 64.5 % and increased to 89.6 % and specificity was 83.3 % and increased to 91.7 %.
These results show the importance of a computational tool to assist neuroradiology decisions, especially in critical situations such as the diagnosis of ischemic stroke.
• Diagnosing patients with stroke requires high efficiency to avoid irreversible cerebral damage.
• A computational algorithm was proposed to enhance the visual perception of stroke.
• Observers’ performance was increased with the aid of enhanced images.
KeywordsStroke Brain Algorithms Tomography Early diagnosis
Alberta Stroke Program Early CT Score
Central Processing Unit
Digital Imaging and Communications in Medicine
Magnetic resonance image
Non-enhanced computed tomography
The authors wish to thank all clinical personnel of the Botucatu Medical School Radiodiagnostic facility. We also thank the Laboratories I3MTO from University of Orleans and LAFAR from São Paulo State University.
Compliance with ethical standards
The scientific guarantor of this publication is José Ricardo de Arruda Miranda from São Paulo State University, Brazil.
Conflict of interest
The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.
Statistics and biometry
No complex statistical methods were necessary for this paper.
Written informed consent was not required for this study because all CT scans used were retrospective and no confidential patient information was used throughout this study.
Institutional Review Board approval was obtained.
• diagnostic or prognostic study
• performed at one institution
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