Prediction of histopathological outcome using averaged multimodal information in rat

Weizhao Zhao, Myron Ginsberg, Ludmila Belayev, Jessie Truettner, Rainald Schmidt-Kastner

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Commonly used autoradiographic image analysis for stroke research has been restricted to the assessment of local cerebral blood flow (LCBF), glucose utilization (LCMRglc) or messenger RNA (mRNA) (by in situ hybridization) in individual brains, with repeated measurements from the same animal. Histopathological analysis of perfusion-fixed paraffin-embedded brain material has long been regarded as the `gold standard' for the quantitative assessment of tissue injury in experimental models of cerebral ischemia. It is desirable to reveal the interrelationship between signals measured at the time of ischemia and the final distribution of cell damage. In this study, averaged images for each modality were derived from individual rats and infarction frequency distribution maps were generated. A single-layer perceptron learning machine with linear and non-linear discriminant functions were constructed to function as a predictive model. The original infarction frequency distribution map and predicted frequency map are presented.

Original languageEnglish (US)
Title of host publicationAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
EditorsH.K. Chang, Y.T. Zhang
PublisherIEEE
Pages2082-2087
Number of pages6
Volume4
StatePublished - 1998
EventProceedings of the 1998 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Part 4 (of 6) - Hong Kong, China
Duration: Oct 29 1998Nov 1 1998

Other

OtherProceedings of the 1998 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Part 4 (of 6)
CityHong Kong, China
Period10/29/9811/1/98

Fingerprint

Rats
Brain
Paraffin
Paraffins
Image analysis
Glucose
Learning systems
Animals
Blood
Cells
Tissue
Neural networks
Messenger RNA

ASJC Scopus subject areas

  • Bioengineering

Cite this

Zhao, W., Ginsberg, M., Belayev, L., Truettner, J., & Schmidt-Kastner, R. (1998). Prediction of histopathological outcome using averaged multimodal information in rat. In H. K. Chang, & Y. T. Zhang (Eds.), Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings (Vol. 4, pp. 2082-2087). IEEE.

Prediction of histopathological outcome using averaged multimodal information in rat. / Zhao, Weizhao; Ginsberg, Myron; Belayev, Ludmila; Truettner, Jessie; Schmidt-Kastner, Rainald.

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. ed. / H.K. Chang; Y.T. Zhang. Vol. 4 IEEE, 1998. p. 2082-2087.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhao, W, Ginsberg, M, Belayev, L, Truettner, J & Schmidt-Kastner, R 1998, Prediction of histopathological outcome using averaged multimodal information in rat. in HK Chang & YT Zhang (eds), Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. vol. 4, IEEE, pp. 2082-2087, Proceedings of the 1998 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Part 4 (of 6), Hong Kong, China, 10/29/98.
Zhao W, Ginsberg M, Belayev L, Truettner J, Schmidt-Kastner R. Prediction of histopathological outcome using averaged multimodal information in rat. In Chang HK, Zhang YT, editors, Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. Vol. 4. IEEE. 1998. p. 2082-2087
Zhao, Weizhao ; Ginsberg, Myron ; Belayev, Ludmila ; Truettner, Jessie ; Schmidt-Kastner, Rainald. / Prediction of histopathological outcome using averaged multimodal information in rat. Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. editor / H.K. Chang ; Y.T. Zhang. Vol. 4 IEEE, 1998. pp. 2082-2087
@inproceedings{f264192a0c854a8b8194d41d0947ff49,
title = "Prediction of histopathological outcome using averaged multimodal information in rat",
abstract = "Commonly used autoradiographic image analysis for stroke research has been restricted to the assessment of local cerebral blood flow (LCBF), glucose utilization (LCMRglc) or messenger RNA (mRNA) (by in situ hybridization) in individual brains, with repeated measurements from the same animal. Histopathological analysis of perfusion-fixed paraffin-embedded brain material has long been regarded as the `gold standard' for the quantitative assessment of tissue injury in experimental models of cerebral ischemia. It is desirable to reveal the interrelationship between signals measured at the time of ischemia and the final distribution of cell damage. In this study, averaged images for each modality were derived from individual rats and infarction frequency distribution maps were generated. A single-layer perceptron learning machine with linear and non-linear discriminant functions were constructed to function as a predictive model. The original infarction frequency distribution map and predicted frequency map are presented.",
author = "Weizhao Zhao and Myron Ginsberg and Ludmila Belayev and Jessie Truettner and Rainald Schmidt-Kastner",
year = "1998",
language = "English (US)",
volume = "4",
pages = "2082--2087",
editor = "H.K. Chang and Y.T. Zhang",
booktitle = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",
publisher = "IEEE",

}

TY - GEN

T1 - Prediction of histopathological outcome using averaged multimodal information in rat

AU - Zhao, Weizhao

AU - Ginsberg, Myron

AU - Belayev, Ludmila

AU - Truettner, Jessie

AU - Schmidt-Kastner, Rainald

PY - 1998

Y1 - 1998

N2 - Commonly used autoradiographic image analysis for stroke research has been restricted to the assessment of local cerebral blood flow (LCBF), glucose utilization (LCMRglc) or messenger RNA (mRNA) (by in situ hybridization) in individual brains, with repeated measurements from the same animal. Histopathological analysis of perfusion-fixed paraffin-embedded brain material has long been regarded as the `gold standard' for the quantitative assessment of tissue injury in experimental models of cerebral ischemia. It is desirable to reveal the interrelationship between signals measured at the time of ischemia and the final distribution of cell damage. In this study, averaged images for each modality were derived from individual rats and infarction frequency distribution maps were generated. A single-layer perceptron learning machine with linear and non-linear discriminant functions were constructed to function as a predictive model. The original infarction frequency distribution map and predicted frequency map are presented.

AB - Commonly used autoradiographic image analysis for stroke research has been restricted to the assessment of local cerebral blood flow (LCBF), glucose utilization (LCMRglc) or messenger RNA (mRNA) (by in situ hybridization) in individual brains, with repeated measurements from the same animal. Histopathological analysis of perfusion-fixed paraffin-embedded brain material has long been regarded as the `gold standard' for the quantitative assessment of tissue injury in experimental models of cerebral ischemia. It is desirable to reveal the interrelationship between signals measured at the time of ischemia and the final distribution of cell damage. In this study, averaged images for each modality were derived from individual rats and infarction frequency distribution maps were generated. A single-layer perceptron learning machine with linear and non-linear discriminant functions were constructed to function as a predictive model. The original infarction frequency distribution map and predicted frequency map are presented.

UR - http://www.scopus.com/inward/record.url?scp=0032276738&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0032276738&partnerID=8YFLogxK

M3 - Conference contribution

VL - 4

SP - 2082

EP - 2087

BT - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

A2 - Chang, H.K.

A2 - Zhang, Y.T.

PB - IEEE

ER -