Parallel Implementation of FCM-Based Volume Segmentation of 3D Images

被引：0

作者：

AlZu'bi, Shadi ^{[1
]}

Shehab, Moahmmed A. ^{[2
]}

Al-Ayyoub, Mahmoud ^{[2
]}

Benkhelifa, Elhadj ^{[3
]}

Jararweh, Yaser ^{[2
]}

机构：

[1] Zaytoonah Univ Jordan, Amman, Jordan

[2] Jordan Univ Sci & Technol, Irbid, Jordan

[3] Staffordshire Univ, Stafford, England

来源：

2016 IEEE/ACS 13TH INTERNATIONAL CONFERENCE OF COMPUTER SYSTEMS AND APPLICATIONS (AICCSA) | 2016年

关键词：

C-MEANS ALGORITHM; FUZZY; GPU;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Parallel programming has many benefits that can help developers and researchers to improve the performance of some algorithms to become more efficient in real life. This is especially true for systems involving medical images. Image segmentation for volume extraction is a famous segmentation process that takes long time to finish execution. In this paper, we consider a new version of the Fuzzy C-Means (FCM) segmentation algorithm (known as IT2FPCM) and provide a parallel implementation of it that is 12X time faster than the sequential implementation. The considered algorithm is based on Interval Type-2 FCM and combines fuzzy and possibilistic ideas in order to obtain higher accuracy. We conduct our experiments using two different machines and the results show that the improvement gains for both machines 11X and12X, respectively.

引用

页数：6

共 50 条

[1] Parallel implementation for 3D medical volume fuzzy segmentation
AlZu'bi, Shadi
Shehab, Mohammed
Al-Ayyoub, Mahmoud
Jararweh, Yaser
Gupta, Brij
[J]. PATTERN RECOGNITION LETTERS, 2020, 130 : 312 - 318
[2] A Modified FCM-Based Brain Lesion Segmentation Scheme for Medical Images
Gautam, Anjali
Sadhya, Debanjan
Raman, Balasubramanian
[J]. PROCEEDINGS OF 3RD INTERNATIONAL CONFERENCE ON COMPUTER VISION AND IMAGE PROCESSING, CVIP 2018, VOL 2, 2020, 1024 : 149 - 159
[3] FCM-based image segmentation with kernel functions
Tang Xinting
Zhang Xiaofeng
Gao Hongjiang
Liu Kun
[J]. 2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND ENGINEERING (CSE) AND IEEE/IFIP INTERNATIONAL CONFERENCE ON EMBEDDED AND UBIQUITOUS COMPUTING (EUC), VOL 1, 2017, : 916 - 919
[4] FCM-Based Method for MRI Segmentation of Anatomical Structure
Antonio, Pinti
[J]. BIOINFORMATICS AND BIOMEDICAL ENGINEERING (IWBBIO 2016), 2016, 9656 : 175 - 183
[5] An efficient FCM-based method for image refinement segmentation
Qi, Yueshuang
Zhang, Anxin
Wang, Hua
Li, Xuemei
[J]. VISUAL COMPUTER, 2022, 38 (07): : 2499 - 2514
[6] An efficient FCM-based method for image refinement segmentation
Yueshuang Qi
Anxin Zhang
Hua Wang
Xuemei Li
[J]. The Visual Computer, 2022, 38 : 2499 - 2514
[7] Segmentation of MR images for 3D volume reconstruction
Masero, V
Silva, AM
León-Rojas, JM
Moreno, J
[J]. METMBS'01: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON MATHEMATICS AND ENGINEERING TECHNIQUES IN MEDICINE AND BIOLOGICAL SCIENCES, 2001, : 458 - 462
[8] MS lesions segmentation in 3D MR images using FCM and SVM
Merzoug, Amina
Benamrane, Nacera
Taleb Ahmed, Abdelmalik
[J]. 2014 4TH INTERNATIONAL CONFERENCE ON IMAGE PROCESSING THEORY, TOOLS AND APPLICATIONS (IPTA), 2014, : 29 - 33
[9] Parallel volume projection in 3D medical images
Larrazabal, G
Escalona, P
Montilla, G
Torrealba, V
Acuna, M
Barrios, V
[J]. SIMULATION MODELLING IN BIOENGINEERING, 1996, : 209 - 216
[10] The application of FCM-based computer image segmentation technology in agricultural production
Liao, Heng
Huang, Huadong
[J]. SERVICE ORIENTED COMPUTING AND APPLICATIONS, 2024,

← 1 2 3 4 5 →