System and method for spectral-based disease detection

A method comprising:

• transmitting broadband light through a fluid confined within a test cassette;
• dispersing the broadband light, after passing through the test cassette, onto a plurality of pixel detectors forming a detector array;
• reading an array of raw spectral values from the detector array;
• deconvolving, based on a spectral response of each of the plurality of pixel detectors, the array of raw spectral values to generate an array of deconvolved spectral values;
• feeding the array of deconvolved spectral values into a trained machine-learning model that processes the array of deconvolved spectral values to obtain an indication of the presence of one or more constituents in the fluid;
• and
• outputting the indication.

A system comprising:

• a light source operable to emit broadband light;
• a cassette holder that is:
• shaped to receive a test cassette that confines a fluid;
• and
• positioned such that the broadband light, when emitted by the light source, passes through the test cassette;
• a first spectrometer that, in response to receiving a first portion of the broadband light after the broadband light has passed through the test cassette, disperses a first wavelength range of the first portion of the broadband light onto a first plurality of pixel detectors forming a first detector array;
• a second spectrometer that, in response to receiving a second portion of the broadband light after the broadband light has passed through the test cassette, disperses a second wavelength range of the second portion of the broadband light onto a second plurality of pixel detectors forming a second detector array;
• a digitizer that is electrically connected to the first and second detector arrays, the digitizer being operable to:
• read a first array of raw spectral values from the first detector array;
• and
• read a second array of raw spectral values from the second detector array;
• and
• a signal processing circuit programmed to:
• deconvolve, based on a spectral response of each of the first and second pluralities of pixel detectors, the first and second arrays of raw spectral values to generate an array of deconvolved spectral values;
• feed the array of deconvolved spectral values into a trained machine-learning model that processes the array of deconvolved spectral values to obtain an indication of the presence of one or more constituents in the fluid;
• and
• output the indication.

A method comprising:

• transmitting broadband light through a fluid confined within a test cassette;
• dispersing a first wavelength range of the broadband light, after passing through the test cassette, onto a first plurality of pixel detectors forming a first detector array;
• dispersing a second wavelength range of the broadband light, after passing through the test cassette, onto a second plurality of pixel detectors forming a second detector array;
• reading a first array of raw spectral values from the first detector array;
• reading a second array of raw spectral values from the second detector array;
• deconvolving, based on a spectral response of each pixel detector of the first and second pluralities of pixel detectors, the first and second arrays of raw spectral values to generate an array of deconvolved spectral values;
• feeding the array of deconvolved spectral values into a trained machine-learning model that processes the array of deconvolved spectral values to obtain an indication of the presence of one or more constituents in the fluid;
• and
• outputting the indication.

A system comprising:

• a first light source operable to emit a first broadband light beam;
• a second light source operable to emit a second broadband light beam;
• a cassette holder that is:
• shaped to receive a test cassette that confines a fluid;
• and
• positioned such that the first and second broadband light beams, when emitted by the respective first and second light sources, pass through the test cassette;
• a first spectrometer that, in response to receiving the first broadband light beam after the first broadband light beam has passed through the test cassette, disperses the first broadband light beam onto a first plurality of pixel detectors forming a first detector array;
• a second spectrometer that, in response to receiving the second broadband light beam after the second broadband light beam has passed through the test cassette, disperses the second broadband light beam onto a second plurality of pixel detectors forming a second detector array;
• a digitizer that is electrically connected to the first and second detector arrays, the digitizer being operable to:
• read a first array of raw spectral values from the first detector array;
• and
• read a second array of raw spectral values from the second detector array;
• and
• a signal processing circuit programmed to:
• deconvolve, based on a spectral response of each of the first and second pluralities of pixel detectors, the first and second arrays of raw spectral values to obtain an array of deconvolved spectral values;
• feed the array of deconvolved spectral values into a trained machine-learning model that processes the array of deconvolved spectral values to obtain an indication of the presence of one or more constituents in the fluid;
• and
• output the indication.

A method comprising:

• constructing a kernel matrix of a spectrometer, wherein:
• the kernel matrix comprises a plurality of cells;
• each cell of the plurality of cells is indexed by a first index value of a plurality of first index values and a second index value of a plurality of second index values;
• the first index value uniquely identifies one of a plurality of pixel detectors of the spectrometer;
• and
• the second index value uniquely identifies one of a plurality of reference wavelengths;
• wherein said constructing comprises, for each pixel detector of the plurality of pixel detectors:
• constructing a spectral response function based at least on (i) one of a plurality of central wavelengths corresponding to said each pixel detector and (ii) one of a plurality of spectral widths corresponding to said each pixel detector;
• evaluating the spectral response function at the plurality of reference wavelengths to obtain a pixel-response vector;
• and
• inserting the pixel-response vector into the kernel matrix.