Machine learning combined with multispectral infrared imaging to guide cancer surgery SPIEtweets
Each pixel in the image cube represents a six-element spectrum. These spectra were normalized using four different approaches: no normalization; max normalization ; area under the curve =1 ; and standard normal variate normalization .
For visualization, images captured using consecutive filters were subtracted to create a “band image” containing signal from a narrow band of wavelengths. For example, a 900-nm band image was produced by subtracting the image captured with a 950-nm long-pass filter from the image captured with an 850-nm long-pass filter, and thus contained signal from the range 850 to 950 nm.
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