A review of graph-based methods for image analysis in digital histopathology

Harshita Sharma, Norman Zerbe, Sebastian Lohmann, Klaus Kayser, Olaf Hellwich, Peter Hufnagl

Abstract


Digital image analysis of histological datasets is a currently expanding field of research. With different stains, magnifications and types of tissues, histological images are inherently complex in nature and contain a wide variety of visual information. Several image analysis techniques are being explored in this direction. However, graph-based methods are gaining most popularity, as these methods can describe tissue architecture and provide adequate numeric information for subsequent computer-based analysis. Graphs have the ability to represent spatial arrangements and neighborhood relationships of different tissue components, which are essential characteristics observed visually by pathologists during investigation of specimens. In this paper, we present a comprehensive review of the graph-based methods explored so far in digital histopathology. We also discuss the current limitations and suggest future directions in graph-based tissue image analysis.

Keywords


Digital histopathology, graph-based methods, whole slide images, medical image analysis, image understanding, tissue architecture, spatial arrangement

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References


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DOI: http://dx.doi.org/10.17629/www.diagnosticpathology.eu-2015-1:61

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Copyright (c) 2015 Harshita Sharma, Norman Zerbe, Sebastian Lohmann, Klaus Kayser, Olaf Hellwich, Peter Hufnagl

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