Photo by CennaLab
First of all, please watch the slides on the top
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We are pushing the limits of AI by inventing a scanner for detecting cancerous cells from medical images using Neural Networks. this patented capture technology is an automated scanner for medical images which enables pathological experts to work remotely with laboratory microscopes from home or anywhere with internet access. The process of scanning consists of
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Iterating the slides and captures high-quality images using super-resolution cameras.
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Stitching the captured images regarding to camera movement error in microscopic scale.
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give images to our deep neural networks for diagnosis purposes.
We benefit from our own built dataset in training purposes. I am in the Computer Vision team and have contributed to Stitching, PapSmear Cancer Classification, Cell Segmentation, Cell Counting, Streaming in Python and C++.
Amir-Hossein Shahidzadeh
PhD Student
My research is at the intersection of Robot Perception and Reinforcement Learning.