Riken Corporation

Chung Yuan Christian University

Topcon Corporation

Tohoku University

Tokai National Higher Education and Research System

Mitsubishi Precision Co., Ltd.

University of the Ryukyus

New X-National Technology K.k.

Hideo Yokota

Akitake Makinouchi

Ming-Dar Tsai

Kuniya Abe

Yuan-Hsiang Chang

Toshiro Higuchi

Ryutaro Himeno

Slo-Li Chu

Masahiro Akiba

Shigeki Suzuki

Masahiro Anzai

Yutaka Yamagata

Suguru Miyagawa

Hidetoshi Katori

Toru Nakazawa

Masao Takamoto

Masato Ogata

Manabu Nagasaka

Kenji Yamazawa

Hideo Sakamoto

Guangzhou An

Kentaro Takanami

Kazuko Omodaka

Yoshinori Hasegawa

Takashi Ijiri

Sakiko Nakamura

Atsushi Yoshiki

Hiroo Yabe

Taketoshi Mishima

Ichiro Ushijima

Takehiro Tawara

Kazuhiro Fujisaki

Yoshimune Shiratori

Naomichi Furushiro

Masashi Iwabuchi

Yusuke Ohya

Norio Yamashita

Shintaro Oyama

Shin Yoshizawa

Daisuke Hirooka

Hiroyuki Shimai

Taiki Furukawa

Yuko Oho

Kazuro Shimokawa

Satoko Takemoto

To provide a three-dimensional hardness distribution measurement method with better measurement accuracy. The method is a three-dimensional hardness distribution measurement method including and repeating: cutting evenly a surface of a member to be measured; imaging the surface having been cut; and pushing an indenter for a hardness test into a plurality of points on the surface having been imaged. In the method, a cutting depth of the surface is controlled, in the cutting, to a predetermined constant amount, and indentation depths of the indenter at the plurality of points are controlled, in the pushing, to a predetermined constant amount.

Three-dimensional hardness distribution measurement method and three-dimensional hardness distribution measurement system

Disclosed herein are a system for identifying cells on a microscopic image. According to some embodiments, the system comprises a non-transitory processor-readable medium, and a processor communicably configured to receive the microscopic image, and process the received microscopic image with a convolutional neural network (CNN) model having a modified U-Net architecture. Also disclosed herein are methods for identifying a spatial pattern of human induced pluripotent stem cells (hiPSCs) by using the present system.

Systems for identifying cells and uses thereof

Provided is a system that enables training for catheter surgery without using radiation. The system offering training for catheter surgery includes: a light source; a blood vessel model to which a catheter having a fluorescent agent applied thereto is inserted; a tank in which the blood vessel model is placed; a filter for rejecting white light that is not transmitted through the blood vessel model, of illuminating light from the light source; a camera for imaging fluorescence transmitted through the filter; a driver for changing the attitude of the light source; and a computer that performs a process of reversing black and white of an image signal output from the camera.

Training apparatus, catheter, image processing method, program, and information recording medium

Provided according to an embodiment of the present disclosure is a radiation shieldincluding a shield wall surrounding a hollow region capable of accommodating therein atoms for an optical lattice clock, the shield wall having, provided therein, at least two apertures communicating with outside. A geometrical shape of an inner wall surface of the shield wall is configured such that a difference between BBR shifts found under two conditions does not exceed a predetermined value over a range of position of atoms, the BBR shifts being caused in atomsby emitted radiation emitted by the inner wall surface, incoming radiation leaking in from the outside through the apertures, and a reflection component of the emitted radiation and incoming radiation at the inner wall surface, the two conditions being a condition where the inner wall surface exhibits mirror reflection and a condition where the inner wall surface exhibits diffuse reflection, the range being where clock transition operation is carried out in the optical lattice clock, the inner wall surface facing the hollow region. Provided according to other embodiments of the present disclosure also are the optical lattice clockincluding such a radiation shield, and a design method for the radiation shield.

Radiation shield and optical lattice clock including radiation shield

An aspect of the present invention allows for more accurately identifying a possible lesion in a human lung field. The aspect of the present invention includes an image obtaining section configured to obtain a chest cross-sectional image of a subject, a segmentation section configured to classify, into a plurality of segments, unit elements of the chest cross-sectional image, and an image dividing section configured to divide the chest cross-sectional image into a plurality of regions. A data deriving section is configured to derive data associated with the possible lesion, the data being derived on the basis of a segment of unit elements in the each region among the plurality of segments. An identifying section is configured to output an identification result, which is a result of identification of the possible lesion in the lung field of the subject.

Identifying device, learning device, method, and storage medium

Target point cloud data about a specific road are extracted from perimeter point cloud data acquired by moving a road surface measurement device along a measurement route and scanning the surroundings thereof. A data storage unit stores trajectory point sequence data that represent, as a plurality of trajectory points, the perimeter point cloud data and a trajectory of the movement of the road surface measurement device. A trajectory point sequence setting unit acquires a trajectory point sequence at equal intervals from the trajectory point sequence data. An extraction area setting unit sets, as extraction areas, a column area Ci and a parallelepiped area Hi that are geometric areas disposed at predetermined positions below a trajectory point Xi. An approximate nearest neighbor search processing unit and an extraction processing unit extract, as the target point cloud data, point data that belong to this extraction area of the perimeter point cloud data.

Point cloud data extraction method and point cloud data extraction device

Disclosed herein are methods for predicting the reprogramming process of cells from a microscopic image of one or more cells. According to some embodiments, the method includes capturing an image of region of interest (ROI) of every pixel of the microscopic image, followed by processing the ROI image with a trained convolutional neural network (CNN) model and a trained long short-term memory (LSTM) network so as to obtain predicted probability maps. Also disclosed herein are a storage medium and a system for executing the present methods.

Method and apparatus for predicting cell reprogramming

An ophthalmic information processing system according to an embodiment includes a receiver and a processor. The receiver receives morphological data of an eye fundus of a subject. In addition, the receiver receives background data of the subject. The processor executes optic nerve head shape classification based on the morphological data and the background data received by the receiver.

Ophthalmic information processing system, ophthalmic information processing method, and recording medium

Disclosed herein are methods for identifying cells undergoing reprogramming and reprogrammed cells from a fluorescence microscopic image of one or more cells. According to some embodiments, the method includes an image processing step, a cell detection step, and, optionally, a clustering step.

Method and apparatus for detecting cell reprogramming

Disclosed herein are methods for analyzing cell kinematics in a nucleated cell culture from a time-series sequence of multiple fluorescence microscopic images of the nucleated cell culture. The method includes the steps of, (a) identifying every cell nucleus in each fluorescence microscopic image; (b) identifying every cell cluster using the cell nuclei identified in the step (a); and (c) tracking the cells and/or cell clusters using the cell nuclei and cell clusters identified for the fluorescence microscopic images in steps (a) and (b) respectively.

Method and apparatus for image processing and visualization for analyzing cell kinematics in cell culture

Medical image data is utilized, physical values are assigned to body parts based on image information, and the target organs are separated from the image data to prepare a 3D biodata model to thereby realize a data model unique to a patient, having an internal structure, and enabling dynamic simulation of a live body. The same target part of a body is captured by CT and MRI to obtain medical images. Sets of pairs of CT images and MRI images are set, a plurality of features showing the same locations are selected and set from the sets of CT images and MRI images, a conversion coefficient between the CT images and MRI images is obtained, and this conversion coefficient is used to rearrange the MRI images by projection transforms and linear interpolation, combine them with the contours of the CT images, and correct their positions in the contours. Further, the images are used to prepare a 3D data model.

Biodata model preparation method and apparatus, data structure of biodata model and data storage device of biodata model, and load dispersion method and apparatus of 3D data model

A region data editing apparatus includes a contour deforming section for receiving a contour deforming operation in which a contour of a region in a three-dimensional image is deformed, a boundary surface deforming section for deforming a boundary surface &#x2202;D between inside and outside of region D in such a manner that the boundary surface &#x2202;D follows the contour deformed by the contour deforming operation, and a region data updating section for updating region data in such a manner that the region data thus updated represents an inside of the boundary surface which has been deformed by the boundary surface deforming section.

Region data editing apparatus, region data editing method, and recording medium

The present invention aims to provide a gene expression image constructing method and a gene expression image constructing system being able to three-dimensionally show expression patterns of a vastly larger number of genes (specifically, about 30,000 genes). In the present invention, a sample is cut, images of sections of the cut sample are picked up and a stereoscopic image of sample, which is a three-dimensional image of the sample, is constructed based on a plurality of picked-up section images, the amount of expression of genes present in the sample is measured based on a plurality of slices prepared when the sample is cut, and a gene expression image in which an expression state of genes present in the sample and a stereoscopic image of sample are associated with each other is constructed based on a predetermined image reconstruction technique from the constructed stereoscopic image of sample and the measured amount of expression.

Gene expression image constructing method and gene expression image constructing system

An artificial bone forming method, comprising a) a powder layer forming step () for forming, into a flat powder layer (), a powder bone material () having biocompatibility and hardening by hydration, b) a partial hardening step () for jetting an aqueous solution () with biocompatibility to a part of the powder layer to harden a jetted portion () by hydration, and c) an artificial bone forming step () for repeating the steps a) and b) for lamination to form a specified artificial bone () of a predetermined three-dimensional structure in which the hardened portions () are connected to each other.

Artificial bone forming method by powder lamination method

Assuming that there are three continuous frames, i.e, cross sectional images of an organism, a dummy region of interest (ROI) is specified manually in the first frame, a temporary ROI is set in the second frame at the same position as that of the dummy ROI in the first frame. Whether a specific region in the second frame is inside or outside of a true ROI is judged based on the initial judgment criterion and values of pixels in the specific region. Whether a specific region in the third frame is inside or outside of the true ROI is judged based on values of pixels of regions that have been judged to be inside the region of interest in the second frame.

Method of extraction of region of interest, image processing apparatus, and computer product

Growing community of inventors

Wako, Japan

Hideo Yokota