Asia Silicon Valley

Entrepreneurship and Commercialization of Giga-Pixel / Tera-Pixel Image Cloud Technology

Principal Investigator:Ching-Wei Wang, Ph.D. of National Taiwan University of Science and Technology
Abstract 

Our team has world-leading technique on real time giga-pixel / tera-pixel image analysis and cloud systems. In comparison to the existing commercial systems, our giga-pixel cloud system is 24 times faster than Leica Aperio Webscope and 117 times faster than Microsoft HDview, which is a huge advantage in real world practice. Our goal is to build a world leading digital pathology cloud system. On top of the cloud platform, various AI models will be added. The ultrafast giga-pixel / tera-pixel cloud platform allows the medical experts to perform diagnosis online and in real time remotely and enables the possibilities to have multiple medical doctors perform diagnosis together even when they are physically not in the same place. The AI models will further provide quantitative information and speed up the diagnosis process.

    • To create an ultrafast giga-pixel / tera-pixel cloud platform for telemedicine and telepathology, providing remote pathological diagnosis services
    • AI deep learning technology: with the professional diagnosis of pathologists, we will develop AI pathological diagnosis modules of various cancers on top of the platform.
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Team Introduction

The PI (Professor Ching-Wei Wang) has built various technologies in gigapixel medical image analysis and AI models in multiple dimensional medical images. In addition, Prof Wang is also a member of Pathological Society of Great Britain and Ireland (Membership No. 00003196) and a member of European Society of Pathology (Membership No. 6928). The co-PIs are experts in veterinary pathology, laboratory animal pathology, and human pathology and pathologists certified by the Chinese Society for Veterinary Pathology and pathologists certified by the ROC, as well as molecular medical specialists of the Taiwanese Society of Molecular Medicine(TSMM).

Goals and Plan
Entry Barrier

Our team has world-leading technique on real time giga-pixel / tera-pixel image analysis and cloud systems. In comparison to the existing commercial systems, our giga-pixel cloud system is 24 times faster than Leica Aperio Webscope and 117 times faster than Microsoft HDview, which is a huge advantage in real world practice. High-speed gigapixel image analysis of cloud display technology, will be a major entry barrier. The technology enables users to perform diagnosis on cell phones and iPad in real time, with the speed as operating under a microscope.

The general market for digital pathology often refers to service and operational analysis of complete slides. However, our team has a profession biotechnology background that allows for more efficient or accurate analysis of biotechnological operations prior to slides. Using immunohistochemical staining, our team can make a complete test on the staining antibodies, staining conditions, staining items and interpretation to achieve the accuracy of the back-end analysis results, and create differentiation and competition thresholds with other competitors.

Market Scope

In recent years, the wisdom of in vitro diagnosis is growing rapidly, especially in the field of pathological diagnosis. Digital Pathology Market is expected to garner $5.7 billion U.S. dollars million by 2020. Digital pathology is an emerging technology in the field of pathology. In the modern methodology, the glass slides containing specimen samples are converted into digital images for easy viewing, analysis, storage, and management of the collected data. This is enabled in part by virtual microscopy, a technology that enables successful image posting and transmission over a connected network. The data-rich image forms the base for maintenance of electronic health records of the patient populace and compile the distributed information to build a central database. The advancements in digital pathology is expected to take the conventional pathology to a more advanced level. Digitalization of pathology has led to the automation of the tests during diagnosis, thus saving cost and efforts. Therefore, the team has a good starting point for future development and is expected to set up a company in 2019.

Video Introduction