TissueMark

Computational pathology

Analyze solid tumor tissue samples in research applications fast and enhance the quality and reliability of macrodissection, nucleic acid extraction, and molecular profiling.

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Accurate and reliable tumor estimation powered by Deep Learning

TissueMark is a key offering in our computational pathology portfolio that assists the user to examine the region of interest for macro dissection by:

Visualizing the region of interest (ROI) and
Indicating the estimated cellular profile in the region of interest

TissueMark enables region of interest detection and cellular profile estimation in digital whole slide images of Lung Histology, Lung Cytology, Breast and Colon2 formalin-fixed paraffin embedded, H&E stained tissue samples. The algorithms are trained to work on Philips iSyntax image format. The application provides three levels of visualization – a macro dissection boundary, a visual heat map of tumor density and, at higher magnification, cellular visualizations. Color-coded, this enables differentiation of the region of interest from stroma, inflammation, lymphocytes and necrosis thereby providing an accurate macro dissection boundary for further molecular testing.

Automated analysis for accurate quantification

TissueMark imaging algorithms automatically annotate the tumor boundary for you. This can be used to provide a tissue map for macrodissection. TissueMark also measures the percent of tumor nuclei to ensure sample quality and sufficient tumor nucleic acid for molecular profiling.

Cost effective

Support streamlining the evaluation of new molecular assays by automating the markup and tumor cell content in H&E samples. This enables you to make the adoption of new molecular tests practical and cost effective.

Instil accuracy and consistency

Opens the pathway to significantly improve workflow and establish accuracy, consistency and quality in molecular pathology.

Improve turnaround time

Biomarker discovery in solid tumors is accelerated, this could significantly speed up the turnaround time for macrodissection in large studies.

Literature

Brochure: TissueMark Brochure
Research Paper: Automated tumor analysis for molecular profiling in lung cancer

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Minimum hardware requirements

CPU	Dual-core @1.65GHz
RAM	3GB of physical RAM memory
Screen Resolution	1024x768
Browser	Firefox (latest), IE (latest), Chrome (latest)
Hard Drive	240GB SATA
Operating system	Most recent web browser
Other software	A PDF reader (e.g. Adobe Acrobat Reader)
Connectivity	100Mbit or 1Gbit Ethernet connection to internet/intranet

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