mSlide - Digital Pathology and Medical Diagnosis Network

Votes: 1
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Biological microscopic imaging technology has important applications in new drug development, cell biology research, tissue pathology analysis, environmental monitoring and other fields. We aim to developing multi-dimensional high resolution digital imaging and analytical instruments for the above mentioned applications.

Based upon existing biological microscope technologies, the project increases functionality through high speed slide loading, continuously scanning images, adaptive continuous focus and fluorescent multi-spectral imaging, while developing a high resolution full slide image acquisition, storage, and software system. This project has also developed application software for disease morphology analysis, tumor fluorescence labeling analysis and botany research. The basic framework for biological tissue characterization database was constructed, and the prototype was applied to bone marrow biopsy, tumor pathology and other practical applications.

The project has realized the key technologies such as automatic tray loading of multiple pathological slides, linear scanning microscopy, adaptive motion focusing, linear magnetic driven XY scanning stage, and piezoelectric driven Z axis with nanometer resolution. Real-time reading and intelligent marking software for ultra high resolution full slide images has been developed, with many pathological databases of diseases having been established, while research into intelligent pathological image analysis and diagnosis based on deep learning is carried out.


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  • Name:
    Shawn Casey
  • Type of entry:
    Team members:
    Shawn Patrick Casey
    Kaijie Wu
    Chaochen Gu
    Xinping Guan
  • Profession:
  • Number of times previously entering contest:
  • Shawn's favorite design and analysis tools:
    LabView, Matlab, CST, Multisim
  • Shawn's hobbies and activities:
    Chess, Foreign Language
  • Shawn belongs to these online communities:
    MSN, QQ
  • Shawn is inspired by:
    A comitment to lifelong learning.
  • Software used for this entry:
  • Patent status: