Abstract: The present disclosure provides methods and systems for ghost cytometry (GC), which may be used to produce an image of an object without using a spatially resolving detector. This may be used to perform image-free ultrafast fluorescence “imaging” cytometry, based on, for example, a single pixel detector. Spatial information obtained from the motion of cells relative to a patterned optical structure may be compressively converted into signals that arrive sequentially at a single pixel detector. Combinatorial use of the temporal waveform with the intensity distribution of the random or pseudo-random pattern may permit computational reconstruction of cell morphology. Machine learning methods may be applied directly to the compressed waveforms without image reconstruction to enable efficient image-free morphology-based cytometry.

Abstract: An imaging flow cytometer includes: a flow channel in which an observation object flows and a length in a width direction is longer than a length in a height direction; an acoustic element configured to apply acoustic waves as standing waves to the flow channel; a light source that irradiates the flow channel with illumination light; an image sensor configured to image at least a line included in a cross section of the observation object crossing a flow line direction which is a direction in which the observation object flows in the flow channel by measuring or imaging the observation object passing through a position irradiated with the illumination light; and circuitry configured to generate an image in which the observation object is scanned in the flow line direction on the basis of a plurality of captured images acquired by the imaging unit imaging the line in a time series.

Abstract: A mask structure optimization device includes a classification target image size acquisition unit that is configured to acquire a size of a classification target image which is an image including a classification target, a mask size setting unit that is configured to set a size of a mask applied to the classification target image, a brightness detection unit that is configured to detect a brightness of each pixel within the classification target image at a position on an opposite side of the mask from the classification target image, a sum total brightness calculation unit that is configured to calculate the sum total brightness of the each pixel within the classification target image detected by the brightness detection unit, an initial value setting unit that is configured to set an initial value for a mask pattern of the mask, and a movement unit that is configured to relatively move the mask with respect to the classification target image.

Abstract: An imaging flow cytometer includes at least one flow channel through which an observation target flows, a light source which irradiates the flow channel with sheet-like excitation light, an imaging unit which images a specific cross-section of the observation target by imaging fluorescence from the observation target having passed through a position irradiated with the excitation light, and a three-dimensional image generation unit which generates a three-dimensional image of the observation target as a captured image on the basis of a plurality of captured images obtained by cross-sectional imaging by the imaging unit.

Abstract: A cell evaluation system includes physical measurement unit, a database, and evaluation unit. The evaluation unit refers to a relevance stored in the database, searches reference measurement information based on measurement information of a cell newly measured via the physical measurement unit, and evaluates the cell with biological measurement information associated with the searched reference measurement information.

Abstract: A mask structure optimization device includes a classification target image size acquisition unit that is configured to acquire a size of a classification target image which is an image including a classification target, a mask size setting unit that is configured to set a size of a mask applied to the classification target image, a brightness detection unit that is configured to detect a brightness of each pixel within the classification target image at a position on an opposite side of the mask from the classification target image, a sum total brightness calculation unit that is configured to calculate the sum total brightness of the each pixel within the classification target image detected by the brightness detection unit, an initial value setting unit that is configured to set an initial value for a mask pattern of the mask, and a movement unit that is configured to relatively move the mask with respect to the classification target image.

Abstract: A mask structure optimization device includes a classification target image size acquisition unit that is configured to acquire a size of a classification target image which is an image including a classification target, a mask size setting unit that is configured to set a size of a mask applied to the classification target image, a brightness detection unit that is configured to detect a brightness of each pixel within the classification target image at a position on an opposite side of the mask from the classification target image, a sum total brightness calculation unit that is configured to calculate the sum total brightness of the each pixel within the classification target image detected by the brightness detection unit, an initial value setting unit that is configured to set an initial value for a mask pattern of the mask, and a movement unit that is configured to relatively move the mask with respect to the classification target image.

Abstract: The present disclosure provides methods and systems for ghost cytometry (GC), which may be used to produce an image of an object without using a spatially resolving detector. This may be used to perform image-free ultrafast fluorescence “imaging” cytometry, based on, for example, a single pixel detector. Spatial information obtained from the motion of cells relative to a patterned optical structure may be compressively converted into signals that arrive sequentially at a single pixel detector. Combinatorial use of the temporal waveform with the intensity distribution of the random or pseudo-random pattern may permit computational reconstruction of cell morphology. Machine learning methods may be applied directly to the compressed waveforms without image reconstruction to enable efficient image-free morphology-based cytometry.

Abstract: A mask structure optimization device includes a classification target image size acquisition unit that is configured to acquire a size of a classification target image which is an image including a classification target, a mask size setting unit that is configured to set a size of a mask applied to the classification target image, a brightness detection unit that is configured to detect a brightness of each pixel within the classification target image at a position on an opposite side of the mask from the classification target image, a sum total brightness calculation unit that is configured to calculate the sum total brightness of the each pixel within the classification target image detected by the brightness detection unit, an initial value setting unit that is configured to set an initial value for a mask pattern of the mask, and a movement unit that is configured to relatively move the mask with respect to the classification target image.

Abstract: A cell evaluation system includes physical measurement unit, a database, and evaluation unit. The evaluation unit refers to a relevance stored in the database, searches reference measurement information based on measurement information of a cell newly measured via the physical measurement unit, and evaluates the cell with biological measurement information associated with the searched reference measurement information.

Abstract: An imaging flow cytometer includes at least one flow channel through which an observation target flows, a light source which irradiates the flow channel with sheet-like excitation light, an imaging unit which images a specific cross-section of the observation target by imaging fluorescence from the observation target having passed through a position irradiated with the excitation light, and a three-dimensional image generation unit which generates a three-dimensional image of the observation target as a captured image on the basis of a plurality of captured images obtained by cross-sectional imaging by the imaging unit.