Mosaics of whole slides (WS) are a valuable resource for pathologists in order to have the whole sample available at high resolution. The WS mosaic provides pathologists with an overview of the whole sample at a glance, helping them to make a reliable diagnosis. Despite recent solutions exist for creating WS mosaics based, for instance, on automated microscopes with motorized stages or WS scanner, most of the histopathology analysis are still performed in laboratories endowed with standard manual stage microscopes. To enable pathologists to achieve real time WS mosaics even using non automated microscopes, while moving the holder manually, we have developed an original approach that does not exploit any dedicated device. Our method exploits fast feature tracker and frame to frame registration that we implemented on common GPU cards. This choice enables pathologists to build WS in real time, while browsing the sample as they are accustomed to, helping them to identify, locate and digitally annotate lesions fast.

Real-time whole slide mosaicing for non-automated microscopy in histopathology analysis

A. Gherardi;A. Bevilacqua
2012

Abstract

Mosaics of whole slides (WS) are a valuable resource for pathologists in order to have the whole sample available at high resolution. The WS mosaic provides pathologists with an overview of the whole sample at a glance, helping them to make a reliable diagnosis. Despite recent solutions exist for creating WS mosaics based, for instance, on automated microscopes with motorized stages or WS scanner, most of the histopathology analysis are still performed in laboratories endowed with standard manual stage microscopes. To enable pathologists to achieve real time WS mosaics even using non automated microscopes, while moving the holder manually, we have developed an original approach that does not exploit any dedicated device. Our method exploits fast feature tracker and frame to frame registration that we implemented on common GPU cards. This choice enables pathologists to build WS in real time, while browsing the sample as they are accustomed to, helping them to identify, locate and digitally annotate lesions fast.
2012
Proceedings of Histopathology Image Analysis (HIMA 2012) Workshop of the 15th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2012)
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A. Gherardi, A. Bevilacqua
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/630628
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