Analysis methods of CT-scan images for the characterization of the bone texture: First results

被引:19
|
作者
Taleb-Ahmed, A
Dubois, P
Duquenoy, E
机构
[1] Littoral Cote Opale, Lab Anal Syst, F-62228 Calais, France
[2] Ctr Hosp & Reg Lille, Inst Technol Med, F-59000 Lille, France
关键词
characterization of the bone texture; fractal method; three dimensional relief; CT-scan images;
D O I
10.1016/S0167-8655(03)00036-9
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The ultimate objective of the planned work is to propose a way to the characterization of the bone texture from the analysis of CT-scan images. This would assist the discrimination of healthy from pathological subjects. This paper emphasizes a preliminary study concerning the selection of tools for the characterization of the bone texture. The selectivity is lead by the analysis of respective sensitivities of the considered methods. We study here two methods of texture analysis. The first one is based on the fractal geometry whose application to the analysis of texture is well established in literature. The second method is an original one. It is called the "method of the three dimensional relief". (C) 2003 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:1971 / 1982
页数:12
相关论文
共 50 条
  • [11] Developing a Classifier Model for Lung Tumors in CT-scan Images
    Basu, Satrajit
    Hall, Lawrence O.
    Goldgof, Dmitry B.
    Gu, Yuhua
    Kumar, Virendra
    Choi, Jung
    Gillies, Robert J.
    Gatenby, Robert A.
    2011 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2011, : 1306 - 1312
  • [12] Adrenal gland evaluation in septic shock patients: preliminary results of the first CT-scan study
    B Jung
    S Nougaret-Jung
    G Chanques
    S Aufort
    N Claveiras
    N Rossel
    B Gallix
    S Jaber
    Critical Care, 13 (Suppl 1):
  • [13] AUTOMATIC DETECTION AND CLASSIFICATION OF LIVER LESIONS FROM CT-SCAN IMAGES
    Benny, Ria
    Thomas, Tessamma
    2015 Fifth International Conference on Advances in Computing and Communications (ICACC), 2015, : 366 - 370
  • [14] Towards consistent representation for reverse distillation on lung CT-scan images
    Li, Zuoyong
    Xu, Shicheng
    Li, Wei
    Xu, Qingjiang
    Cai, Wenchao
    Wu, Xiang
    BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2025, 107
  • [15] 3D Liver Segmentation from CT-Scan Images
    Sutiratanapong, Nateepat
    Sucontphunt, Tanasai
    PROCEEDINGS OF THE 20TH INTERNATIONAL CONFERENCE ON COMPUTING AND INFORMATION TECHNOLOGY, IC2IT 2024, 2024, 973 : 131 - 140
  • [16] Automatic Classification of COVID-19 using CT-Scan Images
    Reis, Hatice Catal
    ACTA SCIENTIARUM-TECHNOLOGY, 2021, 43
  • [17] ANALYSIS OF BODY-COMPOSITION OF THE ABDOMEN BY CT-SCAN
    INOKUCHI, S
    YAMAOKA, S
    KUMAKURA, H
    JOURNAL OF THE ANTHROPOLOGICAL SOCIETY OF NIPPON, 1990, 98 (02): : 176 - 176
  • [18] Whole body CT-scan vs. selective CT-scan in geriatric trauma: Systematic review and meta-analysis
    Tang, Patrick
    Elkington, Olivia
    Stevens, Sean
    TRAUMA-ENGLAND, 2025,
  • [19] COMPUTER-ANALYSIS OF PERIVENTRICULAR LUCENCY ON THE CT-SCAN
    ASADA, M
    TAMAKI, N
    KANAZAWA, Y
    MATSUMOTO, S
    MATSUO, M
    KIMURA, S
    FUJII, S
    KANEDA, Y
    NEURORADIOLOGY, 1978, 16 : 207 - 211
  • [20] CT-scan data acquisition to generate biomechanical models of bone structures
    Viceconti, M
    Zannoni, C
    Baruffaldi, F
    Pierotti, L
    Toni, A
    Cappello, A
    COMPUTER METHODS IN BIOMECHANICS & BIOMEDICAL ENGINEERING - 2, 1998, : 279 - 287