Clustering-based volume segmentation design

被引:0
|
作者
Xu Q. [1 ]
Zhao Z. [1 ]
Wang W. [1 ]
机构
[1] Shijiazhuang Tiedao University, Shijiazhuang, Hebei Province
关键词
Clustering; Data structure; Interesting data segment; Segmentation; Volumetric;
D O I
10.1504/IJAMC.2016.080962
中图分类号
学科分类号
摘要
A novel volumetric data clustering work introduced in this paper aim to cluster the volume data and filter out its inherent noise via extracting the data structure and indicating the useless segments. On the basis of classic segmentation algorithms, this research focuses on exploring volume-based segmentation solutions and property-oriented display mechanisms to assist with the decision-making stage involved in associated volume data manipulation works. As the resulting outputs of this design, the occlusion relationships embedded into volumetric space can be precisely oriented in the manner of visualised partition feature(s). This data visualisation process can be accomplished automatically based on the classified information. In addition, a novel manipulation operation can be built via extracting wireframe-based surfaces from the segmentation results. Copyright © 2016 Inderscience Enterprises Ltd.
引用
收藏
页码:156 / 166
页数:10
相关论文
共 50 条
  • [41] Convolutional neural network and clustering-based codebook design method for massive MIMO systems
    Jing Xing
    Die Hu
    EURASIP Journal on Advances in Signal Processing, 2022
  • [42] A Clustering-Based Approach to Kinetic Closest Pair
    Zahed Rahmati
    Timothy M. Chan
    Algorithmica, 2018, 80 : 2742 - 2756
  • [43] Clustering-Based Interpretation of Deep ReLU Network
    Picchiotti, Nicola
    Gori, Marco
    AIXIA 2021 - ADVANCES IN ARTIFICIAL INTELLIGENCE, 2022, 13196 : 403 - 412
  • [44] Clustering-based Automated Requirement Trace Retrieval
    Al-walidi, Nejood Hashim
    Azab, Shahira Shaaban
    Khamis, Abdelaziz
    Darwish, Nagy Ramadan
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2022, 13 (12) : 783 - 792
  • [45] Convolutional neural network and clustering-based codebook design method for massive MIMO systems
    Xing, Jing
    Hu, Die
    EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, 2022, 2022 (01)
  • [46] A Clustering-Based Patient Grouper for Burn Care
    Onah, Chimdimma Noelyn
    Allmendinger, Richard
    Handl, Julia
    Yiapanis, Paraskevas
    Dunn, Ken W.
    INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING (IDEAL 2019), PT II, 2019, 11872 : 123 - 131
  • [47] A Clustering-Based Approach to Kinetic Closest Pair
    Rahmati, Zahed
    Chan, Timothy M.
    ALGORITHMICA, 2018, 80 (10) : 2742 - 2756
  • [48] A clustering-based method for unsupervised intrusion detections
    Jiang, SY
    Song, XY
    Wang, H
    Han, JJ
    Li, QH
    PATTERN RECOGNITION LETTERS, 2006, 27 (07) : 802 - 810
  • [49] Clustering-Based Denoising With Locally Learned Dictionaries
    Chatterjee, Priyam
    Milanfar, Peyman
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2009, 18 (07) : 1438 - 1451
  • [50] A Clustering-Based Ensemble Technique for Shape Decomposition
    Lewin, Sergej
    Jiang, Xiaoyi
    Clausing, Achim
    STRUCTURAL, SYNTACTIC, AND STATISTICAL PATTERN RECOGNITION, 2012, 7626 : 153 - 161