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04-16-2016, 02:19 PM
Photonic Time Stretch Microscopy Combined with Artificial Intelligence Spots Cancer Cells in Blood
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UCLA researchers have developed a*new laser-based tech**logy to rapidly screen blood samples for the presence of cancer cells. The label-free system measures 16 different physical characteristics of each cell and analyzes the data to identify whether the cell is cancerous. **t having to introduce any labeling chemicals and being gentle on the cells, the technique leaves the cells alive and available for further inspection using other means.
It relies on a photonic time stretch microscope and a computer that runs deep learning artificial intelligence algorithms. The microscope can take millions of images per second thanks to unusual optics that produce*high quality shots*even at this speed. The deep learning system can actually run a variety of algorithms and the researchers tested a few to see which are better than others at spotting cancer cells.
From the study abstract in Scientific Reports:
Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a **vel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phe**typic diag**sis and better understanding of the heterogeneous gene expressions in cells.
Study in Scientific Reports: Deep Learning in Label-free Cell Classification… (http://www.nature.com/articles/srep21471)
Source: UCLA… (http://newsroom.ucla.edu/releases/microscope-uses-artificial-intelligence-to-find-cancer-cells-more-efficiently)
The post Photonic Time Stretch Microscopy Combined with Artificial Intelligence Spots Cancer Cells in Blood (http://www.medgadget.com/2016/04/photonic-time-stretch-microscopy-combined-with-artificial-intelligence-spots-cancer-cells-in-blood.html) appeared first on Medgadget (http://www.medgadget.com).
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http://www.medgadget.com/wp-content/uploads/2016/04/laser-microscope.jpg
UCLA researchers have developed a*new laser-based tech**logy to rapidly screen blood samples for the presence of cancer cells. The label-free system measures 16 different physical characteristics of each cell and analyzes the data to identify whether the cell is cancerous. **t having to introduce any labeling chemicals and being gentle on the cells, the technique leaves the cells alive and available for further inspection using other means.
It relies on a photonic time stretch microscope and a computer that runs deep learning artificial intelligence algorithms. The microscope can take millions of images per second thanks to unusual optics that produce*high quality shots*even at this speed. The deep learning system can actually run a variety of algorithms and the researchers tested a few to see which are better than others at spotting cancer cells.
From the study abstract in Scientific Reports:
Our system captures quantitative optical phase and intensity images and extracts multiple biophysical features of individual cells. These biophysical measurements form a hyperdimensional feature space in which supervised learning is performed for cell classification. We compare various learning algorithms including artificial neural network, support vector machine, logistic regression, and a **vel deep learning pipeline, which adopts global optimization of receiver operating characteristics. As a validation of the enhanced sensitivity and specificity of our system, we show classification of white blood T-cells against colon cancer cells, as well as lipid accumulating algal strains for biofuel production. This system opens up a new path to data-driven phe**typic diag**sis and better understanding of the heterogeneous gene expressions in cells.
Study in Scientific Reports: Deep Learning in Label-free Cell Classification… (http://www.nature.com/articles/srep21471)
Source: UCLA… (http://newsroom.ucla.edu/releases/microscope-uses-artificial-intelligence-to-find-cancer-cells-more-efficiently)
The post Photonic Time Stretch Microscopy Combined with Artificial Intelligence Spots Cancer Cells in Blood (http://www.medgadget.com/2016/04/photonic-time-stretch-microscopy-combined-with-artificial-intelligence-spots-cancer-cells-in-blood.html) appeared first on Medgadget (http://www.medgadget.com).
http://feeds.feedburner.com/~ff/Medgadget?d=yIl2AUoC8zA (http://feeds.feedburner.com/~ff/Medgadget?a=EWcn6gbUecM:SltaQjk0tns:yIl2AUoC8zA) http://feeds.feedburner.com/~ff/Medgadget?d=qj6IDK7rITs (http://feeds.feedburner.com/~ff/Medgadget?a=EWcn6gbUecM:SltaQjk0tns:qj6IDK7rITs) http://feeds.feedburner.com/~ff/Medgadget?i=EWcn6gbUecM:SltaQjk0tns:gIN9vFwOqvQ (http://feeds.feedburner.com/~ff/Medgadget?a=EWcn6gbUecM:SltaQjk0tns:gIN9vFwOqvQ)
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