A cell analyzer and a sorting method for the cell analyzer are disclosed. Multiple optical signals generated by each of particles irradiated with light in a blood sample in a detection region are collected. The particles includes a first category of particles and a second category of particles. For each of the particles, Intensities of a first group of optical signals, which includes at least two optical signals selected from the multiple optical signals, and a pulse width of a second group of optical signals, which includes at least one optical signal selected from the multiple optical signals are acquired. For each of the particles, one or more reinforcement signals related to the particle are calculated based on an intensity of a first optical signal selected from the first group of optical signals and a pulse width of a second optical signal selected from the second group of optical signals, where the first optical signal is as same as or different from the second optical signal. The first category of particles and the second category of particles are distinguished from each other based at least partially on the one or more reinforcement signals related to each of the particles.

A cell analyzer and a sorting method for the cell analyzer are disclosed. Multiple optical signals generated by each of particles irradiated with light in a blood sample in a detection region are collected. The particles includes a first category of particles and a second category of particles. For each of the particles, Intensities of a first group of optical signals, which includes at least two optical signals selected from the multiple optical signals, and a pulse width of a second group of optical signals, which includes at least one optical signal selected from the multiple optical signals are acquired. For each of the particles, one or more reinforcement signals related to the particle are calculated based on an intensity of a first optical signal selected from the first group of optical signals and a pulse width of a second optical signal selected from the second group of optical signals, where the first optical signal is as same as or different from the second optical signal. The first category of particles and the second category of particles are distinguished from each other based at least partially on the one or more reinforcement signals related to each of the particles.

A system is provided comprising an FTIR spectrometer configured to obtain a Fourier Transformed infrared (FTIR) spectrum of a Peripheral Blood Mononuclear Cells (PBMC) sample of the subject; a data processor operable with the FTIR spectrometer, and configured to analyze the infrared (IR) spectrum of the Peripheral Blood Mononuclear Cells (PBMC) sample of the subject by assessing a characteristic of the sample of the subject at at least one wavenumber; and an output unit, configured to generate an output indicative of the presence of a solid tumor, based on the infrared (IR) spectrum. Other embodiments are also provided.

An apparatus and a method for identifying at least one type of white blood cell (WBC) within a whole blood sample is provided. The method includes: adding at least one colorant to the sample; providing at least one fluorescent excitation light and at least one transmission light; receiving both light fluorescing from and transmitted through the sample and producing signals representative thereof; creating at least one image of the sample using the signals; identifying WBCs within the sample image; quantitatively analyzing at least some of the identified WBCs within the image, including determining one or more quantitative values; and identifying at least one type of WBC from the identified WBCs using the quantitative values.

A microfluidic device for detecting rare cells in a fluid sample comprises the rare cell and other cells. The microfluidic device comprises an inlet for receiving the fluid sample, a labyrinth channel structure in fluid communication with the inlet, and an outlet in fluid communication with the labyrinth channel structure for collecting the rare cells separated from the other cells in the fluid sample. The labyrinth channel structure comprises at least one channel through which the fluid sample flows. The at least one channel has a plurality of segments and a plurality of corners with each corner defined between adjacent segments. The presence of the plurality of corners induces separation of the rare cells from the other cells in the fluid sample as the rare cells move to a first equilibrium position within the at least one channel when a ratio of inertial lift forces (F.sub.Z) and Dean flow (F.sub.D) of the fluid sample is from 2 to 10.

Disclosed in one aspect is a method for performing a complete blood count (CBC) on a sample of whole blood by metering a predetermined amount of the whole blood and mixing it with a predetermined amount of diluent and stain and transferring a portion thereof to an imaging chamber of fixed dimensions and utilizing an automated microscope with digital camera and cell counting and recognition software to count every white blood cell and red blood corpuscle and platelet in the sample diluent/stain mixture to determine the number of red cells, white cells, and platelets per unit volume, and analyzing the white cells with cell recognition software to classify them.

A method for analyzing digital holographic microscopy (DHM) data for hematology applications includes receiving a plurality of DHM images acquired using a digital holographic microscopy system. One or more connected components are identified in each of the plurality of DHM images and one or more training white blood cell images are generated from the one or more connected components. A classifier is trained to identify a plurality of white blood cell types using the one or more training white blood cell images. The classifier may be applied to a new white blood cell image to determine a plurality of probability values, each respective probability value corresponding to one of the plurality of white blood cell types. The new white blood cell image and the plurality of probability values may then be presented in a graphical user interface.

The Intrinsic Hyper-Spectral Flow Cytometer (IHSFC) and its associated methodology, improves current flow cytometry by eliminating the need of associated hardware-based elements currently used for spectral data detection. The (IHSFC), rather than using narrow band lasers to excite or interrogate the analytes, the flow stream is excited by a wide wavelength range beam. The raw data generated by the (IHSFC) are as follows; forward light scatter, right angle light scatter, coherent spectral data and non-coherent spectral data. The intrinsic fluorescent spectral components are extracted from the coherent and non-coherent spectral data.

The present disclosure relates to the field of medical technology, which provides methods and apparatuses for identifying red blood cells infected by plasmodium. The methods may include: obtaining a forward-scattered light signal, a side-scattered light signal and an optional fluorescence signal from cells in a blood sample; obtaining a first two-dimensional scattergram according to the forward-scattered light signal and the side-scattered light signal, or obtaining a three-dimensional scattergram according to the forward-scattered light signal, the side-scattered light signal and the fluorescence signal; and identifying cells located in a predetermined area of the first two-dimensional scattergram or the three-dimensional scattergram as the red blood cells infected by plasmodium. The apparatuses perform the methods. The methods and apparatuses can have better identification accuracy.

Among other things, a first surface is configured to receive a sample and is to be used in a microscopy device. There is a second surface to be moved into a predefined position relative to the first surface to form a sample space that is between the first surface and the second surface and contains at least part of the sample. There is a mechanism configured to move the second surface from an initial position into the predefined position to form the sample space. When the sample is in place on the first surface, the motion of the second surface includes a trajectory that is not solely a linear motion of the second surface towards the first surface.