Towards Improved Epilepsia Diagnosis by Unsupervised Segmentation of Neuropathology Tissue Sections using Ripley’s-L features.

Schoening, Timm , Hans, Volkmar H. and Nattkemper, Tim W. (2011) Towards Improved Epilepsia Diagnosis by Unsupervised Segmentation of Neuropathology Tissue Sections using Ripley’s-L features. [Paper] In: Bildverarbeitung für die Medizin. , 20.-22.03.2011, Lübeck, Germany . Bildverarbeitung für die Medizin 2011. ; pp. 44-48 . DOI 10.1007/978-3-642-19335-4_11.

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Abstract

The analysis of architectural features in neural tissue sections and the identification of distinct regions is challenging for computer aided diagnosis (CAD) in neuropathology. Due to the difficulty of locating a tissue’s origin and alignment as well as the vast variety of structures within such images an orientation independent (i. e. rotation invariant) approach for tissue region segmentation has to be found to encode the structural features of neural layer architecture in the tissue. We propose to apply the Ripley’s-L function, originating from the field of plant ecol- ogy, to compute feature vectors encoding the spatial statistics of point patterns described by selectively stained cells. Combining the Ripley’s- L features with unsupervised clustering enables a segmentation of tissue sections into neuropathological areas.

Document Type: Conference or Workshop Item (Paper)
Date Deposited: 23 May 2017 06:37
Last Modified: 15 Mar 2018 14:14
URI: https://oceanrep.geomar.de/id/eprint/38086

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