Arna van Engelen

Publications (3) View all

• Article: Automated segmentation of atherosclerotic histology based on pattern classification

  A van Engelen, W.J. Niessen, S. Klein, H.C. Groen, K. van Gaalen, H.J.M. Verhagen, J.J. Wentzel, A van der Lugt, M. de Bruijne
  Journal of Pathology Informatics. 03/2013; 4(3).
• Source

  Available from: bigr.nl

  Article: Multi-feature-based plaque characterization in ex vivo MRI trained by registration to 3D histology.

  Arna van Engelen, Wiro J Niessen, Stefan Klein, Harald C Groen, Hence J M Verhagen, Jolanda J Wentzel, Aad van der Lugt, Marleen de Bruijne
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  ABSTRACT: We present a new method for automated characterization of atherosclerotic plaque composition in ex vivo MRI. It uses MRI intensities as well as four other types of features: smoothed, gradient magnitude and Laplacian images at several scales, and the distances to the lumen and outer vessel wall. The ground truth for fibrous, necrotic and calcified tissue was provided by histology and μCT in 12 carotid plaque specimens. Semi-automatic registration of a 3D stack of histological slices and μCT images to MRI allowed for 3D rotations and in-plane deformations of histology. By basing voxelwise classification on different combinations of features, we evaluated their relative importance. To establish whether training by 3D registration yields different results than training by 2D registration, we determined plaque composition using (1) a 2D slice-based registration approach for three manually selected MRI and histology slices per specimen, and (2) an approach that uses only the three corresponding MRI slices from the 3D-registered volumes. Voxelwise classification accuracy was best when all features were used (73.3 ± 6.3%) and was significantly better than when only original intensities and distance features were used (Friedman, p < 0.05). Although 2D registration or selection of three slices from the 3D set slightly decreased accuracy, these differences were non-significant.
  Physics in Medicine and Biology 12/2011; 57(1):241-56. · 2.83 Impact Factor
• Article: A reliable, non-invasive measurement tool for anisotropy in normal skin and scar tissue.

  Pauline D H M Verhaegen, Evelien M Res, Arna van Engelen, Esther Middelkoop, Paul P M van Zuijlen
  [show abstract] [hide abstract]
  ABSTRACT: Anisotropy of the skin varies depending on different locations and pathological conditions. Currently, no reliable non-invasive measurement tool is available for tissue anisotropy. The Reviscometer is an anisotropy measurement tool that measures the resonance running time (RRT) of a shock wave. This study was initiated to establish the reliability of the Reviscometer on normal skin and scars, and to provide basic information on tissue alignment in normal skin and scars. Fifty volunteers and 50 patients underwent measurements on normal skin and scars, respectively. All measurements were performed by the same two observers. Measurements on normal skin were performed on the forearm, upper arm, and abdomen. The results showed that the intraclass correlation coefficient of the inter-observer reliability was > or =0.79 on normal skin and > or =0.86 on scars. In normal skin, the highest mean RRT was found on the abdomen (156.4+/-48.8), followed by the upper arm (123.2+/-33.6) and the forearm (112.5+/-24.3). A significantly lower mean RRT was found in scars (52.3+/-21.9) compared with normal skin (91.6+/-37.7). Reviscometer measurements were reliable for normal skin and scars. In addition, clear differences between scars and normal skin but also within different locations on normal skin were identified. The Reviscometer can be considered for the evaluation of the efficacy of different treatments.
  Skin Research and Technology 08/2010; 16(3):325-31. · 1.71 Impact Factor