Classification of Fundus Images for Diagnosing Glaucoma by Self-Organizing Map and Learning Vector Quantization

被引：0

作者：

Matsuda, Nobuo ^{[1
]}

Laaksonen, Jorma ^{[2
]}

Tajima, Fumiaki ^{[3
]}

Sato, Hideaki ^{[4
]}

机构：

[1] Oshima Coll Maritime Technol Informat Sci & Techn, Yamaguchi 7422193, Japan

[2] Aalto Univ, Lab Comp & Inf Sci, FIN-02015 Espoo, Finland

[3] Yokohama Natl Univ, Educ & Human Sci, Yokohama, Kanagawa 240, Japan

[4] Kyousai Tachikawa HOSP, Fed Natl Public Serv Personnel Mutual Aid Assoc, Tokyo 1900022, Japan

来源：

ADVANCES IN NEURO-INFORMATION PROCESSING, PT II | 2009年 / 5507卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a two stage diagnosis system that consists of Self-Organizing Map (SOM) and Learning Vector Quantization (LVQ) subsystems for diagnosis of fundus images. The first stage performs clustering and pseudo-classification of the input feature data by a SOM. The use of the pseudo-classes is able to improve the performance of the second stage consisting of a LVQ codebook. The proposed system has been tested on real medical treatment image data. In the experiments we have achieved a maximum accuracy rate of 71.2%, which is comparable to other results in literature.

引用

页码：703 / +

页数：2

共 50 条

[1] Fuzzy classification using self-organizing map and learning vector quantization
Chen, N
[J]. DATA MINING AND KNOWLEDGE MANAGEMENT, 2004, 3327 : 41 - 50
[2] Vector quantization of residual images using self-organizing map
YliRantala, E
Ojala, T
Vuorimaa, P
[J]. ICNN - 1996 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS, VOLS. 1-4, 1996, : 464 - 467
[3] Lung Nodules Classification Using Massive-Training Self-Organizing Map and Learning Vector Quantization
Weei, Yan Soon
Pheng, Hang See
[J]. 2019 1ST INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND DATA SCIENCES (AIDAS2019), 2019, : 18 - 22
[4] Predictive self-organizing map for vector quantization of migratory signals
Hirose, A
Nagashima, T
[J]. ARTIFICIAL NEURAL NETWORKS - ICANN 2002, 2002, 2415 : 884 - 889
[5] Dynamic bit allocation in image coding using a Self-Organizing Map with Learning Vector Quantization
Neto, JS
Neto, SD
Nascimento, FAD
[J]. 38TH MIDWEST SYMPOSIUM ON CIRCUITS AND SYSTEMS, PROCEEDINGS, VOLS 1 AND 2, 1996, : 858 - 861
[6] ADAPTIVE LEARNING-METHOD IN SELF-ORGANIZING MAP FOR EDGE-PRESERVING VECTOR QUANTIZATION
KIM, YK
RA, JB
[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 1995, 6 (01): : 278 - 280
[7] Self-organizing maps and learning vector quantization for feature sequences
Somervuo, P
Kohonen, T
[J]. NEURAL PROCESSING LETTERS, 1999, 10 (02) : 151 - 159
[8] Self-Organizing Maps and Learning Vector Quantization for Feature Sequences
Panu Somervuo
Teuvo Kohonen
[J]. Neural Processing Letters, 1999, 10 : 151 - 159
[9] Multistrategy Self-Organizing Map Learning for Classification Problems
Hasan, S.
Shamsuddin, S. M.
[J]. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2011, 2011
[10] On quantization error of self-organizing map network
Sun, Y
[J]. NEUROCOMPUTING, 2000, 34 : 169 - 193

← 1 2 3 4 5 →