Medical image segmentation, volume representation and registration using spheres in the geometric algebra framework

被引:13
作者
Jorge, Rivera-Rovelo [1 ]
Eduardo, Bayro-Corrochano [1 ]
机构
[1] CINVESTAV, Unidad Guadalajara, Dept Elect Engn & Comp Sci, Zapopan 45010, Jalisco, Mexico
关键词
image segmentation; volumetric data representation; marching cubes; non-rigid registration; Delaunay tetrahedrization; conformal geometric algebra;
D O I
10.1016/j.patcog.2006.06.032
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 an algorithm to model volumetric data and other one for non-rigid registration of such models using spheres formulated in the geometric algebra framework. The proposed algorithm for modeling, as opposite to the Union of Spheres method, reduces the number of entities (spheres) used to model 3D data. Our proposal is based in marching cubes idea using, however, spheres, while the Union of Spheres uses Delaunay tetrahedrization. The non-rigid registration is accomplished in a deterministic annealing scheme. At the preprocessing stage we segment the objects of interest by a segmentation method based on texture information. This method is embedded in a region growing scheme. As our final application, we present a scheme for surgical object tracking using again geometric algebra techniques. (c) 2006 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:171 / 188
页数:18
相关论文
共 50 条
  • [21] A Heteromorphous Deep CNN Framework for Medical Image Segmentation Using Local Binary Pattern
    Iqbal, Saeed
    Qureshi, Adnan N.
    IEEE ACCESS, 2022, 10 : 63466 - 63480
  • [22] Framework for Comparison and Evaluation of Image Segmentation Algorithms for Medical Imaging
    Windisch, G.
    Kozlovszky, M.
    VI LATIN AMERICAN CONGRESS ON BIOMEDICAL ENGINEERING (CLAIB 2014), 2014, 49 : 480 - 483
  • [23] CyCoSeg: A Cyclic Collaborative Framework for Automated Medical Image Segmentation
    Medley, Daniela
    Santiago, Carlos
    Nascimento, Jacinto C.
    IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2022, 44 (11) : 8167 - 8182
  • [24] Image segmentation using a mixture of principal components representation
    Dony, RD
    Haykin, S
    IEE PROCEEDINGS-VISION IMAGE AND SIGNAL PROCESSING, 1997, 144 (02): : 73 - 80
  • [25] Medical Image Segmentation Using Transformer Networks
    Karimi, Davood
    Dou, Haoran
    Gholipour, Ali
    IEEE ACCESS, 2022, 10 : 29322 - 29332
  • [26] Medical image segmentation using improved FCM
    Zhang XiaoFeng
    Zhang CaiMing
    Tang WenJing
    Wei ZhenWen
    SCIENCE CHINA-INFORMATION SCIENCES, 2012, 55 (05) : 1052 - 1061
  • [27] Medical image segmentation using improved FCM
    XiaoFeng Zhang
    CaiMing Zhang
    WenJing Tang
    ZhenWen Wei
    Science China Information Sciences, 2012, 55 : 1052 - 1061
  • [28] Medical image segmentation using improved FCM
    ZHANG XiaoFeng 1
    2 School of Information and Electrical Engineering
    3 School of Computer Science and Technology
    4 Shandong Province Key Lab of Digital Media Technology
    ScienceChina(InformationSciences), 2012, 55 (05) : 1052 - 1061
  • [29] Biomedical image segmentation using geometric deformable models and metaheuristics
    Mesejo, Pablo
    Valsecchi, Andrea
    Marrakchi-Kacem, Linda
    Cagnoni, Stefano
    Damas, Sergio
    COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, 2015, 43 : 167 - 178
  • [30] Weakly-Supervised 3D Medical Image Segmentation Using Geometric Prior and Contrastive Similarity
    Du, Hao
    Dong, Qihua
    Xu, Yan
    Liao, Jing
    IEEE TRANSACTIONS ON MEDICAL IMAGING, 2023, 42 (10) : 2936 - 2947