Objective and reproducible segmentation and quantification of tuberous sclerosis lesions in FLAIR brain MR images

Tanja Alderliesten; Wiro J. Niessen; Koen L. Vincken; J. B. Antoine Maintz; Floor Jansen; Onno van Nieuwenhuizen; Max A. Viergever

doi:10.1117/12.431033

3 July 2001 Objective and reproducible segmentation and quantification of tuberous sclerosis lesions in FLAIR brain MR images

Tanja Alderliesten, Wiro J. Niessen, Koen L. Vincken, J. B. Antoine Maintz, Floor Jansen, Onno van Nieuwenhuizen, Max A. Viergever

Author Affiliations +

Proceedings Volume 4322, Medical Imaging 2001: Image Processing; (2001) https://doi.org/10.1117/12.431033
Event: Medical Imaging 2001, 2001, San Diego, CA, United States

Abstract

A semi-automatic segmentation method for Tuberous Sclerosis (TS) lesions in the brain has been developed. Both T1 images and Fluid Attenuated Inversion Recovery (FLAIR) images are integrated in the segmentation procedure. The segmentation procedure is mainly based on the notion of fuzzy connectedness. This approach uses the two basic concepts of adjacency and affinity to form a fuzzy relation between voxels in the image. The affinity is defined using two quantities that are both based on characteristics of the intensities in the lesion and surrounding brain tissue (grey and white matter). The semi-automatic method has been compared to results of manual segmentation. Manual segmentation is prone to interobserver and intraobserver variability. This was especially true for this particular study, where large variations were observed, which implies that a golden standard for comparison was not available. The method did perform within the variability of the observers and therefore has the potential to improve reproducibility of quantitative measurements.

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Tanja Alderliesten, Wiro J. Niessen, Koen L. Vincken, J. B. Antoine Maintz, Floor Jansen, Onno van Nieuwenhuizen, and Max A. Viergever "Objective and reproducible segmentation and quantification of tuberous sclerosis lesions in FLAIR brain MR images", Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); https://doi.org/10.1117/12.431033

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