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Proceedings Paper

A sparse representation of the pathologist's interaction with whole slide images to improve the assigned relevance of regions of interest
Author(s): Daniel Santiago; Germán Corredor; Eduardo Romero
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Paper Abstract

During a diagnosis task, a Pathologist looks over a Whole Slide Image (WSI), aiming to find out relevant pathological patterns. Nonetheless, a virtual microscope captures these structures, but also other cellular patterns with different or none diagnostic meaning. Annotation of these images depends on manual delineation, which in practice becomes a hard task. This article contributes a new method for detecting relevant regions in WSI using the routine navigations in a virtual microscope. This method constructs a sparse representation or dictionary of each navigation path and determines the hidden relevance by maximizing the incoherence between several paths. The resulting dictionaries are then projected onto each other and relevant information is set to the dictionary atoms whose similarity is higher than a custom threshold. Evaluation was performed with 6 pathological images segmented from a skin biopsy already diagnosed with basal cell carcinoma (BCC). Results show that our proposal outperforms the baseline by more than 20%.

Paper Details

Date Published: 17 November 2017
PDF: 7 pages
Proc. SPIE 10572, 13th International Conference on Medical Information Processing and Analysis, 1057204 (17 November 2017); doi: 10.1117/12.2285906
Show Author Affiliations
Daniel Santiago, Univ. Nacional de Colombia (Colombia)
Institución Univ. Politéenico Grancolombiano (Colombia)
Germán Corredor, Univ. Nacional de Colombia (Colombia)
Eduardo Romero, Univ. Nacional de Colombia (Colombia)

Published in SPIE Proceedings Vol. 10572:
13th International Conference on Medical Information Processing and Analysis
Eduardo Romero; Natasha Lepore; Jorge Brieva; Juan David García, Editor(s)

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