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Z-score Mapping Method for Extracting Hypoattenuation Areas of Hyperacute Stroke in Unenhanced CT
- Source :
- Academic Radiology. 17:84-92
- Publication Year :
- 2010
- Publisher :
- Elsevier BV, 2010.
-
Abstract
- The purpose of this study was to develop a z-score mapping method on the basis of a voxel-by-voxel analysis to visualize hypoattenuation areas of hyperacute stroke on unenhanced computed tomographic (CT) images.The algorithm of the developed method consisted of five main steps: anatomic standardization, the construction of a normal reference database, calculation of the z scores, the elimination of false-positive areas, and the extraction of hypoattenuation areas. The obtained z-score map was then superimposed on the original CT images for identifying hypoattenuation areas of hyperacute stroke on the unenhanced CT images. The method was applied to 21 patients with infarctions of the middle cerebral artery territory3 hours after symptom onset. The performance of the method was evaluated using receiver-operating characteristic analysis.Hypoattenuation regions could be significantly distinguished from normal regions by z-score values (P.0001). The area under the receiver-operating characteristic curve for distinction between 68 hypoattenuation regions and 142 normal regions was 0.834.The developed method has the potential to accurately indicate high-signal intensity areas corresponding to hypoattenuation areas on CT images in the hyperacute stage of stroke.
- Subjects :
- Male
medicine.medical_specialty
Contrast Media
Standard score
Sensitivity and Specificity
Pattern Recognition, Automated
Computed tomographic
Artificial Intelligence
medicine.artery
medicine
Cluster Analysis
Humans
Radiology, Nuclear Medicine and imaging
Acute ischemic stroke
Stroke
Aged
Aged, 80 and over
Hypoattenuation
business.industry
Reproducibility of Results
Middle Aged
medicine.disease
Radiographic Image Enhancement
Hyperacute stroke
Acute Disease
Middle cerebral artery
Reference database
Radiographic Image Interpretation, Computer-Assisted
Female
Radiology
Tomography, X-Ray Computed
business
Algorithms
Subjects
Details
- ISSN :
- 10766332
- Volume :
- 17
- Database :
- OpenAIRE
- Journal :
- Academic Radiology
- Accession number :
- edsair.doi.dedup.....3c7694e8e181f0068c0c545039246bb6
- Full Text :
- https://doi.org/10.1016/j.acra.2009.07.011