Hamamatsu-Photonics K.k.

Hamamatsu University School of Medicine

Kyoto University

Social Welfare Corporation Seirei Social Welfare Community

National University Corporation Hamamatsu University School of Medicine

Hidenao Yamada

Toyohiko Yamauchi

Osamu Yasuhiko

Daisuke Yamashita

Tadashi Fukami

Fumio Hashimoto

Kibo Ote

Shigetoshi Okazaki

Hirotoshi Kikuchi

Kentaro Goto

Amane Hirotsu

Hisayuki Matsui

Norikazu Sugiyama

Norio Nakatsuji

Yoshinori Mizuguchi

Kozo Takeuchi

Yusuke Ozaki

Satoshi Hirakawa

Yumi Kakuno

Akira Obana

An observation apparatus includes a light source unit, an irradiation optical system, an imaging optical system, a modulation unit, an imaging unit, an analysis unit, beam splitters and, and mirrors. The analysis unit obtains a real part of a function χ(t)=log[1+U(t)/U(t)], defined by time series data U(t) of a complex amplitude image of object light on an imaging plane and time series data U(t) of a complex amplitude image of reference light on the imaging plane, based on time series data I(t) of an intensity image of interference light on the imaging plane and time series data I(t) of an intensity image of the reference light on the imaging plane. Further, the analysis unit obtains an imaginary part of χ(t) from the real part of χ(t) using the Kramers-Kronig relations, and further obtains U(t).

Observation device and observation method using a low-speed camera as an imaging unit when observing a moving observation object

An observation apparatus includes a light source, a mirror, a condenser lens, an objective lens, a beam splitter, an imaging unit, and an analysis unit. The analysis unit includes an interference intensity image acquisition unit, a first complex amplitude image generation unit, a second complex amplitude image generation unit, a phase conjugate operation unit, a two-dimensional phase image generation unit, a three-dimensional phase image generation unit, and a refractive index distribution calculation unit. The analysis unit irradiates an observation object with light along each of a plurality of light irradiation directions by changing an orientation of a reflection surface of the mirror, acquires an interference intensity image at a reference position for each of the plurality of light irradiation directions from the imaging unit, and performs necessary processing based on the interference intensity images to obtain a three-dimensional phase image of the observation object.

Observation device and observation method

An ocular fundus image processing device acquires a first image generated by irradiating an ocular fundus of a subject with excitation light of a blue wavelength and a second image generated by irradiating the ocular fundus with excitation light of a green wavelength, generates three trained models for predicting a correction factor for calculating a quantity of macular pigment of the subject from input images including the first image and the second image through training using three different initial values, predicts three correction factors by inputting the input images including the first image and the second image to the three trained models, calculates a statistical value of the three correction factors and derives the statistical value as the correction factor of the subject, and calculates a quantity of macular pigment of the subject on the basis of the first image and the correction factor of the subject.

Ocular fundus image processing method, ocular fundus image processing device, ocular fundus image processing program, and recording medium having said program recorded thereon

The method includes an acquisition step for model generation of acquiring a hologram for model generation in which an image of a cell is captured and which is used to generate a learning model, a generation step for model generation of generating a new hologram for model generation having a different focal position from the acquired hologram for model generation and increasing the number of holograms for model generation, and a learning model generation step of generating a learning model by performing machine learning using the increased holograms for model generation.

Learning model generation method, identification method, learning model generation system, identification system, and non-transitory computer-readable storage medium

A cell observation system observes a cell moving in a flow path with a fluid, and includes a first imaging apparatus, a second imaging apparatus, and a control device. The first imaging apparatus includes a first optical system and a first imaging element, and captures an image of the cell at a first position in a moving direction. The second imaging apparatus includes a second optical system, in which a focus is adjusted based on a focus adjustment signal, and a second imaging element, and captures an image of the cell at a second position downstream of the first position. The control device obtains a passing position of the cell in a cross section of the flow path based on the image obtained by the first imaging element, generates the focus adjustment signal, and provides the signal to the second optical system.

Cell observation system and cell observation method

An interference image acquisition apparatus includes a light source, a beam splitter, a second reflection mirror, an imager, and a first reflection mirror. A cell is placed on one side of a transparent material, and the first reflection mirror is placed on the other side of the transparent material. In a two-beam interferometer, an optical path difference between an optical path length of a first light beam reflected by the first reflection mirror and an optical path length of a second light beam reflected by the second reflection mirror is set to a coherence length of light output from the light source or less. The imager acquires an interference image in a state in which the cell is placed at a position conjugate to an imaging plane in a first optical system between the imaging plane and the first reflection mirror.

Interference image acquiring device and method for acquiring interference image

An evaluation method is a method for evaluating a cell mass containing a plurality of aggregated cells, and includes an imaging step of capturing an image of light obtained from the cell mass by irradiating the cell mass with light, an analysis step of setting a reference point for the cell mass included in image data obtained by the imaging step, setting sampling circles centered on the reference point, and determining a parameter for a state of the cell mass based on image data included in regions on the sampling circles, and an evaluation step of evaluating the cell mass based on the parameter.

Cell mass evaluation method and device for analyzing state of cell mass

Cover for culture vessel

A cell observation system observes a cell moving in a flow path with a fluid, and includes a first observation apparatus, a second observation apparatus, and a control device. The first observation apparatus includes an objective lens and a line camera. The second observation apparatus includes an objective lens and an area camera. The control device analyzes first imaging data output from the first observation apparatus to determine whether the cell satisfies a specific condition, instructs the area camera to output second imaging data of the cell determined to satisfy the specific condition, and analyzes the second imaging data output from the second observation apparatus to determine whether the cell is a specific cell.

A fluorescence measurement apparatus includes a fluorescence image acquisition unit that acquires a fluorescence image containing an object, an interference image acquisition unit that acquires an interference image containing the object, and an operation unit. The operation unit determines an optical thickness image based on the interference image acquired by the interference image acquisition unit, and determines, in a region of interest set in common in both of the fluorescence image acquired by the fluorescence image acquisition unit and the optical thickness image, a fluorescence expression rate of the object based on an integrated value of a fluorescence intensity in the fluorescence image and an integrated value of an optical thickness in the optical thickness image.

Fluorescence measurement device and fluorescence measurement method

An interference observation apparatus includes a light source, a splitting beam splitter, a combining beam splitter, a mirror, a beam splitter, a mirror, a piezo element, a stage, a photodetector, an image acquisition unit, and a current control unit. An interference optical system from the splitting beam splitter to the combining beam splitter forms a Mach-Zehnder interferometer. The current control unit controls a wavelength of laser light output from the light source to adjust a phase difference between two split light components at the combining by the combining beam splitter.

Interference observation device and interference observation method

A measurement apparatus includes an interference image acquisition unit, a fluorescence image acquisition unit, an operation unit, and a timing control circuit. The operation unit generates an optical thickness image based on an interference image acquired by the interference image acquisition unit, generates a mask image showing a region in which pixel values in a fluorescence image acquired by the fluorescence image acquisition unit are larger than a threshold value, and determines an integrated value of an optical thickness in the region shown by the mask image in the optical thickness image.

Measurement apparatus and measurement method

The present invention relates to a cell determination method for determining a cell type based on a content of glycogen in a cell, including: an acquisition step of acquiring optical path length data by measuring an optical path length of the cell; a calculation step of calculating an optical path length indicator correlated with the optical path length of the cell from the obtained optical path length data; a comparison step of comparing the calculated optical path length indicator with a threshold; and a determination step of determining whether the cell is a cell type having a high glycogen content in the cell or a cell type having a low glycogen content in the cell, based on the comparison result.

Cell determination method, cell determination device and cell determination program

An observation apparatus observes an observation object moving in a flow path with a fluid, and includes a light source, a splitting unit, a combining unit, a collimator, a cylindrical lens, an objective lens, a collimator, a cylindrical lens, an objective lens, a modulation unit, an imaging unit, an analysis unit, and the like. The imaging unit includes a plurality of pixels arranged in a direction intersecting with a moving direction of an image of the observation object on a light receiving plane on which the image of the observation object moving in the flow path is formed, and receives combined light output from the combining unit to repeatedly output a detection signal indicating a one-dimensional interference image. The analysis unit generates a two-dimensional image of the observation object on the basis of the detection signal.

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Hamamatsu, Japan

Hidenao Yamada