Segmentation of medical images by using wavelet transform and incremental self-organizing map

被引：0

作者：

Dokur, Zumray ^{[1
]}

Iscan, Zafer ^{[1
]}

Olmez, Tamer ^{[1
]}

机构：

[1] Istanbul Tech Univ, Elect & Commun Engn, TR-34469 Istanbul, Turkey

来源：

MICAI 2006: ADVANCES IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS | 2006年 / 4293卷

关键词：

segmentation of medical images; artificial neural networks; self-organizing map; wavelet transform;

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 novel method that uses incremental self-organizing map (ISOM) network and wavelet transform together for the segmentation of magnetic resonance (MR), computer tomography (CT) and ultrasound (US) images. In order to show the validity of the proposed scheme, ISOM has been compared with Kohonen's SOM. Two-dimensional continuous wavelet transform (2D-CWT) is used to form the feature vectors of medical images. According to the selected two feature extraction methods, features are formed by the intensity of the pixel of interest or mean value of intensities at one neighborhood of the pixel at each sub-band. The first feature extraction method is used for MR and CT head images. The second method is used for US prostate image.

引用

页码：800 / +

页数：3

共 50 条

[1] Heart sound classification using wavelet transform and incremental self-organizing map
Dokur, Zuemray
Olmer, Tamer
[J]. DIGITAL SIGNAL PROCESSING, 2008, 18 (06) : 951 - 959
[2] Medical image categorization based on wavelet transform and Self-Organizing Map
da Silva, Leandro Augusto
Moreno, Ramon Alfredo
Furuie, Sergio Shiguemi
Hernandez, Emilio Del Moral
[J]. PROCEEDINGS OF THE 7TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS DESIGN AND APPLICATIONS, 2007, : 353 - +
[3] Segmentation of multispectral MR images using a hierarchical self-organizing map
Bhandarkar, SM
Nammalwar, P
[J]. FOURTEENTH IEEE SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS, PROCEEDINGS, 2001, : 294 - 299
[4] Exploiting the self-organizing map for medical image segmentation
Chang, Ping-Lin
Teng, Wei-Guang
[J]. TWENTIETH IEEE INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS, PROCEEDINGS, 2007, : 281 - +
[5] Segmentation for Brain Magnetic Resonance Images Using Dual-Tree Complex Wavelet Transform and Spatial Constrained Self-Organizing Tree Map
Zhang, Jingdan
Jiang, Wuhan
[J]. INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, 2014, 24 (03) : 208 - 214
[6] QRS Complex Analysis Using Wavelet Transform and Two Layered Self-Organizing Map
Kaneko, Mutsuo
Gotho, Takafumi
Iseri, Fumiaki
Takeshita, Kotaro
Ohki, Hidehiro
Sueda, Naomichi
[J]. 2011 COMPUTING IN CARDIOLOGY, 2011, 38 : 813 - 816
[7] A Multiscale Approach to Automatic Medical Image Segmentation Using Self-Organizing Map
马峰
夏绍玮
[J]. Journal of Computer Science & Technology, 1998, (05) : 402 - 409
[8] A multiscale approach to automatic medical image segmentation using self-organizing map
Feng Ma
Shaowei Xia
[J]. Journal of Computer Science and Technology, 1998, 13 (5) : 402 - 409
[9] Wavelet and self-organizing map declacker
Tuzman, A
[J]. ARCHIVING, RESTORATION, AND NEW METHODS OF RECORDING, 2001, : 206 - 210
[10] Color segmentation in multicolor images using node-growing self-organizing map
Ouyang, Wenbin
Xu, Bugao
Yuan, Xiaohui
[J]. COLOR RESEARCH AND APPLICATION, 2019, 44 (02): : 184 - 193

← 1 2 3 4 5 →