IEICE TRANSACTIONS on Information
A Separation of Electroretinograms for Diabetic Retinopathy
Summary :
The electroretinogram (ERG) is used to diagnose many kinds of eye diseases. Our final purpose in this paper is a detection of diabetic retinopathy by using only ERG. In this paper, we describe a method to examine whether presented ERG data belong to a group of diabetic retinopathy. The ERG mainly consists of the a-wave, the b-wave and the oscillatory potential (op-wave). It was known that the op-wave varies as progress of retinopathy. Thus, we use the latency, the amplitude and the peak frequency of the op-wave. First, we study these features of sample ERG data, statistically. It was clarified that some of these characteristics are significantly different between a normal group and a group of diabetic retinopathy. By using some of these characteristics, we classify unknown ERG data on the basis of the Mahalanobis' generalized distance or the linear discriminant function. The highest accuracy of this method for the unknown data is about 92.73%.
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- IEICE TRANSACTIONS on Information Vol.E78-D No.8 pp.1087-1092
- Publication Date
- 1995/08/25
- Publicized
- Online ISSN
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- Type of Manuscript
- PAPER
- Category
- Medical Electronics and Medical Information
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Yutaka MAEDA, Takayuki AKASHI, Yakichi KANATA, "A Separation of Electroretinograms for Diabetic Retinopathy" in IEICE TRANSACTIONS on Information,
vol. E78-D, no. 8, pp. 1087-1092, August 1995, doi: .
Abstract: The electroretinogram (ERG) is used to diagnose many kinds of eye diseases. Our final purpose in this paper is a detection of diabetic retinopathy by using only ERG. In this paper, we describe a method to examine whether presented ERG data belong to a group of diabetic retinopathy. The ERG mainly consists of the a-wave, the b-wave and the oscillatory potential (op-wave). It was known that the op-wave varies as progress of retinopathy. Thus, we use the latency, the amplitude and the peak frequency of the op-wave. First, we study these features of sample ERG data, statistically. It was clarified that some of these characteristics are significantly different between a normal group and a group of diabetic retinopathy. By using some of these characteristics, we classify unknown ERG data on the basis of the Mahalanobis' generalized distance or the linear discriminant function. The highest accuracy of this method for the unknown data is about 92.73%.
URL: https://global.ieice.org/en_transactions/information/10.1587/e78-d_8_1087/_p
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@ARTICLE{e78-d_8_1087,
author={Yutaka MAEDA, Takayuki AKASHI, Yakichi KANATA, },
journal={IEICE TRANSACTIONS on Information},
title={A Separation of Electroretinograms for Diabetic Retinopathy},
year={1995},
volume={E78-D},
number={8},
pages={1087-1092},
abstract={The electroretinogram (ERG) is used to diagnose many kinds of eye diseases. Our final purpose in this paper is a detection of diabetic retinopathy by using only ERG. In this paper, we describe a method to examine whether presented ERG data belong to a group of diabetic retinopathy. The ERG mainly consists of the a-wave, the b-wave and the oscillatory potential (op-wave). It was known that the op-wave varies as progress of retinopathy. Thus, we use the latency, the amplitude and the peak frequency of the op-wave. First, we study these features of sample ERG data, statistically. It was clarified that some of these characteristics are significantly different between a normal group and a group of diabetic retinopathy. By using some of these characteristics, we classify unknown ERG data on the basis of the Mahalanobis' generalized distance or the linear discriminant function. The highest accuracy of this method for the unknown data is about 92.73%.},
keywords={},
doi={},
ISSN={},
month={August},}
Copy
TY - JOUR
TI - A Separation of Electroretinograms for Diabetic Retinopathy
T2 - IEICE TRANSACTIONS on Information
SP - 1087
EP - 1092
AU - Yutaka MAEDA
AU - Takayuki AKASHI
AU - Yakichi KANATA
PY - 1995
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E78-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 1995
AB - The electroretinogram (ERG) is used to diagnose many kinds of eye diseases. Our final purpose in this paper is a detection of diabetic retinopathy by using only ERG. In this paper, we describe a method to examine whether presented ERG data belong to a group of diabetic retinopathy. The ERG mainly consists of the a-wave, the b-wave and the oscillatory potential (op-wave). It was known that the op-wave varies as progress of retinopathy. Thus, we use the latency, the amplitude and the peak frequency of the op-wave. First, we study these features of sample ERG data, statistically. It was clarified that some of these characteristics are significantly different between a normal group and a group of diabetic retinopathy. By using some of these characteristics, we classify unknown ERG data on the basis of the Mahalanobis' generalized distance or the linear discriminant function. The highest accuracy of this method for the unknown data is about 92.73%.
ER -
English
