Medical Image Segmentation using Particle Swarm Optimization

被引：0

作者：

Ait-Aoudia, Samy ^{[1
]}

Guerrout, El-Hachemi ^{[1
]}

Mahiou, Ramdane ^{[1
]}

机构：

[1] ESI Ecole Natl Super Informat, Algiers 16270, Algeria

来源：

2014 18TH INTERNATIONAL CONFERENCE ON INFORMATION VISUALISATION (IV) | 2014年

关键词：

Medical image segmentation; Hidden Markov Random Field; Swarm Particles Optimization; Kappa Index;

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：

Segmentation of medical images is one of the fundamental problems in image processing field. It aims to provide a crucial decision support to physicians. There are several methods to perform segmentation. Hidden Markov Random Fields (HMRF) constitutes an elegant way to model the problem of segmentation. This modelling leads to the minimization of an energy function. In this paper we focus on Particles Swarm Optimization (PSO) method to solve this optimization problem. The quality of segmentation is evaluated on grounds truths images using the Kappa index. The results show the supremacy of the HMRF-PSO method compared to Kmeans and threshold based techniques.

引用

页码：287 / 291

页数：5

共 50 条

[31] Hidden Markov Random Fields and Swarm Particles: a Winning Combination in Image Segmentation [J].

Guerrout, El-Hachemi ;

Mahiou, Ramdane ;

Ait-Aoudia, Samy .

INTERNATIONAL CONFERENCE ON FUTURE INFORMATION ENGINEERING (FIE 2014), 2014, 10 :19-24

[32] Intuitionistic level set segmentation for medical image segmentation [J].

Arora J. ;

Tushir M. .

Recent Advances in Computer Science and Communications, 2020, 13 (05) :1039-1046

[33] Medical image segmentation using rough set and local polynomial regression [J].

Cong-Hua Xie ;

Yong-Jun Liu ;

Jin-Yi Chang .

Multimedia Tools and Applications, 2015, 74 :1885-1914

[34] μ-Net: Medical image segmentation using efficient and effective deep supervision [J].

Yuan, Di ;

Xu, Zhenghua ;

Tian, Biao ;

Wang, Hening ;

Zhan, Yuefu ;

Lukasiewicz, Thomas .

COMPUTERS IN BIOLOGY AND MEDICINE, 2023, 160

[35] Medical image segmentation using rough set and local polynomial regression [J].

Xie, Cong-Hua ;

Liu, Yong-Jun ;

Chang, Jin-Yi .

MULTIMEDIA TOOLS AND APPLICATIONS, 2015, 74 (06) :1885-1914

[36] Efficient Medical Image Segmentation Using Probabilistic KNN Label Downsampling [J].

Ali, Shahzad ;

Khan, Muhammad Salman ;

Lee, Yu Rim ;

Park, Soo Young ;

Tak, Won Young ;

Jung, Soon Ki .

40TH ANNUAL ACM SYMPOSIUM ON APPLIED COMPUTING, 2025, :186-193

[37] Medical Image Segmentation using a Multi-Agent System Approach [J].

Chitsaz, Mahsa ;

Seng, Woo Chaw .

INTERNATIONAL ARAB JOURNAL OF INFORMATION TECHNOLOGY, 2013, 10 (03) :222-229

[38] Pairwise learning for medical image segmentation [J].

Wang, Renzhen ;

Cao, Shilei ;

Ma, Kai ;

Zheng, Yefeng ;

Meng, Deyu .

MEDICAL IMAGE ANALYSIS, 2021, 67

[39] Shortcut Learning in Medical Image Segmentation [J].

Lin, Manxi ;

Weng, Nina ;

Mikolaj, Kamil ;

Bashir, Zahra ;

Svendsen, Morten B. S. ;

Tolsgaard, Martin G. ;

Christensen, Anders N. ;

Feragen, Aasa .

MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2024, PT VIII, 2024, 15008 :623-633

[40] JOINT ATTENTION FOR MEDICAL IMAGE SEGMENTATION [J].

Zhang, Mo ;

Dong, Bin ;

Li, Quanzheng .

2022 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (IEEE ISBI 2022), 2022,

← 1 2 3 4 5 →