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Valuing vicinity: Memory attention framework for context-based semantic segmentation in histopathology

Ester, Oliver; Hörst, Fabian; Seibold, Constantin ORCID iD icon 1; Keyl, Julius; Ting, Saskia; Vasileiadis, Nikolaos; Schmitz, Jessica; Ivanyi, Philipp; Grünwald, Viktor; Bräsen, Jan Hinrich; Egger, Jan; Kleesiek, Jens
1 Institut für Anthropomatik und Robotik (IAR), Karlsruher Institut für Technologie (KIT)

Abstract:

The segmentation of histopathological whole slide images into tumourous and non-tumourous types of tissue is a challenging task that requires the consideration of both local and global spatial contexts to classify tumourous regions precisely. The identification of subtypes of tumour tissue complicates the issue as the sharpness of separation decreases and the pathologist’s reasoning is even more guided by spatial context. However, the identification of detailed tissue types is crucial for providing personalized cancer therapies. Due to the high resolution of whole slide images, existing semantic segmentation methods, restricted to isolated image sections, are incapable of processing context information beyond. To take a step towards better context comprehension, we propose a patch neighbour attention mechanism to query the neighbouring tissue context from a patch embedding memory bank and infuse context embeddings into bottleneck hidden feature maps. Our memory attention framework (MAF) mimics a pathologist’s annotation procedure — zooming out and considering surrounding tissue context. The framework can be integrated into any encoder–decoder segmentation method. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000159092
Veröffentlicht am 28.06.2023
Originalveröffentlichung
DOI: 10.1016/j.compmedimag.2023.102238
Scopus
Zitationen: 2
Web of Science
Zitationen: 1
Dimensions
Zitationen: 4
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Anthropomatik und Robotik (IAR)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 07.2023
Sprache Englisch
Identifikator ISSN: 0895-6111, 1879-0771
KITopen-ID: 1000159092
Erschienen in Computerized Medical Imaging and Graphics
Verlag Elsevier
Band 107
Seiten Art.-Nr.: 102238
Nachgewiesen in Dimensions
Web of Science
Scopus
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