Journal of Pathology Informatics Journal of Pathology Informatics
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SYMPOSIUM - ORIGINAL RESEARCH
Year : 2013  |  Volume : 4  |  Issue : 2  |  Page : 9

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


1 ARCES-Advanced Research Center on Electronic Systems, University of Bologna, Italy
2 ARCES-Advanced Research Center on Electronic Systems, DISI Department of Computer Science and Engineering, University of Bologna, Italy

Correspondence Address:
Alessandro Bevilacqua
ARCES-Advanced Research Center on Electronic Systems, DISI Department of Computer Science and Engineering, University of Bologna
Italy
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Source of Support: None, Conflict of Interest: None


PMID: 23766945

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Context: Mosaics of Whole Slides (WS) are a valuable resource for pathologists 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. Nowadays, there are lots of dedicated devices and hardware to achieve WS automatically and in batch, but only few of them are conceived to work tightly connected with a microscope and none of them is capable of working in real-time with common light microscopes. However, there is a need of having low-cost yet effective mosaicing applications even in small laboratories to improve routine histopathological analyses or to perform remote diagnoses. Aims: The purpose of this work is to study and develop a real-time mosaicing algorithm working even using non-automated microscopes, to enable pathologists to achieve WS while moving the holder manually, without exploiting any dedicated device. 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. Materials and Methods: Our method exploits fast feature tracker and frame to frame registration that we implemented on common graphics processing unit cards. The system work with common light microscopes endowed with a digital camera and connected to a commodity personal computer. Result and Conclusion: The system has been tested on several histological samples to test the effectiveness of the algorithm to work with mosaicing having different appearances as far as brightness, contrast, texture, and detail levels are concerned, attaining sub-pixel registration accuracy at real-time interactive rates.


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