Image-based algorithm for the catheter recognition based on GLCM

V. V. Danilov, I. P. Skirnevskiy, R. A. Manakov, O. M. Gerget, F. Melgani

Research output: Contribution to conferencePaperpeer-review


The focus of this study was to develop an image-based algorithm for the catheter detection. Epicardial full-volume 3D echocardiography datasets were used as an input data of the algorithm. In total, 9 datasets consisted of 15 three-dimensional timeframes were processed. To correctly detect the catheter, the feature-based approach was applied to recognition the catheter within the 3D echocardiography datasets. The algorithm based on gray-level co-occurrence matrix (GLCM) was applied as a feature extraction technique. Once the GLCM was computed, we obtained correlation, contrast, homogeneity and energy features. Then we applied feature thresholds to the catheter detection. These thresholds were obtained using Support Vector Machine (SVM) with the linear kernel function and standardization the predictor data. The average segmentation and recognition accuracies of the algorithm equal 94.16% and 87.2% respectively. The processing time for one 2D slice and one 3D dataset are equal to 9±0.2 milliseconds and 1.96±0.045 seconds, respectively. Though the algorithm is not time-consuming for 2D mode, it is still complicated to apply it for real-time surgery in 3D mode.

Original languageEnglish
Number of pages6
Publication statusPublished - 2018
Event28th International Conference on Computer Graphics and Vision, GraphiCon 2018 - Tomsk, Russian Federation
Duration: 24 Sep 201827 Sep 2018


Conference28th International Conference on Computer Graphics and Vision, GraphiCon 2018
CountryRussian Federation


  • Catheter recognition
  • Echocardiography
  • GLCM
  • Texture analysis
  • Tracking

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition

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