JP2019141090A5 - - Google Patents

Download PDF

Info

Publication number
JP2019141090A5
JP2019141090A5 JP2019087392A JP2019087392A JP2019141090A5 JP 2019141090 A5 JP2019141090 A5 JP 2019141090A5 JP 2019087392 A JP2019087392 A JP 2019087392A JP 2019087392 A JP2019087392 A JP 2019087392A JP 2019141090 A5 JP2019141090 A5 JP 2019141090A5
Authority
JP
Japan
Prior art keywords
embryo
image
state
blastomeres
selection system
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
JP2019087392A
Other languages
Japanese (ja)
Other versions
JP7000379B2 (en
JP2019141090A (en
Filing date
Publication date
Application filed filed Critical
Priority to JP2019087392A priority Critical patent/JP7000379B2/en
Priority claimed from JP2019087392A external-priority patent/JP7000379B2/en
Publication of JP2019141090A publication Critical patent/JP2019141090A/en
Publication of JP2019141090A5 publication Critical patent/JP2019141090A5/ja
Application granted granted Critical
Publication of JP7000379B2 publication Critical patent/JP7000379B2/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Description

本発明は、上述の課題の少なくとも一部を解決するためになされたものであり、以下の形態として実現することが可能である。第1の態様は、胚選抜システムとしての態様である。この胚培養システムは、培養容器に設けられた複数のウェルに収容され培養されている胚を、設定された時間間隔で撮像した前記ウェル毎の画像を、時系列的に格納する画像格納部と、前記画像格納部に格納された前記画像を読み出して、前記画像における前記胚の割球数の経時的な変化を解析することによって前記胚の状態を判定する判定部と、を備え、前記判定部は、受精処理されてから開始される最初の卵割において、前記胚の割球数が2個の状態に直接移行したことを確認した場合と、受精処理されてから開始される最初の卵割において、前記胚の割球数が2個の状態を経ることなく前記胚の割球数が3個以上の状態に直接移行した場合とで、前記胚について異なる判定を行なう。
また、第2の態様は、胚を選抜する方法としての態様である。この胚選抜方法は、培養容器に設けられた複数のウェルに収容され培養されている胚を、設定された時間間隔で撮像した前記ウェル毎の画像を、時系列的に格納する画像格納工程と、前記画像格納工程で格納された前記画像を読み出して、前記画像における前記胚の割球数の経時的な変化を解析することによって胚を選抜する選抜工程と、を備え、前記選抜工程において、受精処理されてから開始される最初の卵割において、前記胚の割球数が2個の状態に直接移行したことを確認したか、あるいは受精処理されてから開始される最初の卵割において、前記胚の割球数が2個の状態を経ることなく前記胚の割球数が3個以上の状態に直接移行したか、によって前記胚を選抜する。
The present invention has been made to solve at least a part of the above-mentioned problems, and can be realized as the following forms. The first aspect is an aspect as an embryo selection system. This embryo culture system includes an image storage unit that stores images of the embryos housed and cultured in a plurality of wells provided in a culture container at set time intervals for each well in chronological order. The determination unit is provided with a determination unit for determining the state of the embryo by reading the image stored in the image storage unit and analyzing the change in the number of blastomeres of the embryo in the image with time. In the first egg splitting started after the fertilization process, the part confirmed that the number of blastomeres of the embryo directly shifted to the two state, and the first egg split started after the fertilization process. In the split, different determinations are made for the embryo depending on whether the number of blastomeres of the embryo directly shifts to the state of 3 or more without going through the state of 2.
The second aspect is an aspect as a method for selecting embryos. This embryo selection method includes an image storage step of storing images of the embryos housed and cultured in a plurality of wells provided in a culture container at set time intervals for each well in chronological order. A selection step of reading out the image stored in the image storage step and selecting an embryo by analyzing a change in the number of blastomeres of the embryo in the image over time is provided, and the selection step includes. In the first cleavage started after the fertilization process, it was confirmed that the number of blastomeres of the embryo directly shifted to the two state, or in the first cleavage started after the fertilization treatment, The embryo is selected depending on whether the number of blastomeres of the embryo directly shifts to the state of 3 or more without going through the state of 2 blastomeres.

Claims (6)

胚選抜システムであって、
培養容器に設けられた複数のウェルに収容され培養されている胚を、設定された時間間隔で撮像した前記ウェル毎の画像を、時系列的に格納する画像格納部と、
前記画像格納部に格納された前記画像を読み出して、前記画像における前記胚の割球数の経時的な変化を解析することによって前記胚の状態を判定する判定部と、
を備え
前記判定部は、受精処理されてから開始される最初の卵割において、前記胚の割球数が2個の状態に直接移行したことを確認した場合と、受精処理されてから開始される最初の卵割において、前記胚の割球数が2個の状態を経ることなく前記胚の割球数が3個以上の状態に直接移行した場合とで、前記胚について異なる判定を行なう、胚選抜システム。
Embryo selection system
An image storage unit that stores images of embryos housed and cultured in a plurality of wells provided in a culture container in a time-series manner for each well, which are images taken at set time intervals.
A determination unit for determining the state of the embryo by reading out the image stored in the image storage unit and analyzing a change in the number of blastomeres of the embryo in the image over time.
Equipped with a,
In the first cleavage started after the fertilization process, the determination unit confirms that the number of blastomeres of the embryo has directly shifted to the two state, and the first cleavage process is started after the fertilization process. In the cleavage of the embryo, different judgments are made for the embryo depending on whether the number of blastomeres of the embryo directly shifts to the state of 3 or more without going through the state of 2 blastomeres. system.
請求項1に記載の胚選抜システムであって、
前記判定部は、教師あり学習によって前記画像に写った前記胚の特徴について学習し、前記学習に基づいて前記胚の状態を判定する、胚選抜システム。
The embryo selection system according to claim 1.
The determination unit is an embryo selection system that learns the characteristics of the embryo captured in the image by supervised learning and determines the state of the embryo based on the learning.
請求項1に記載の胚選抜システムであって、
前記判定部は、多層のニューラルネットワークを用いたディープラーニングによって前記画像に写った前記胚の特徴について学習し、前記学習に基づいて前記胚の状態を判定する、胚選抜システム。
The embryo selection system according to claim 1.
The determination unit is an embryo selection system that learns the characteristics of the embryo captured in the image by deep learning using a multi-layer neural network and determines the state of the embryo based on the learning.
請求項1から請求項3までのいずれか一項に記載の胚選抜システムであって、さらに、
前記画像のうち判定に用いられた判定画像を報知する報知部を備える、胚選抜システム。
The embryo selection system according to any one of claims 1 to 3, and further.
An embryo selection system including a notification unit for notifying a determination image used for determination among the images.
請求項4に記載の胚選抜システムであって、
前記報知部は、前記判定画像を報知するとともに前記判定画像において前記判定部が判定の根拠とした情報を報知する、胚選抜システム。
The embryo selection system according to claim 4.
The notification unit is an embryo selection system that notifies the determination image and also notifies the information on which the determination unit is based in the determination image.
を選抜する方法であって、
培養容器に設けられた複数のウェルに収容され培養されている胚を、設定された時間間隔で撮像した前記ウェル毎の画像を、時系列的に格納する画像格納工程と、
前記画像格納工程で格納された前記画像を読み出して、前記画像における前記胚の割球数の経時的な変化を解析することによって胚を選抜する選抜工程と、
を備え
前記選抜工程において、受精処理されてから開始される最初の卵割において、前記胚の割球数が2個の状態に直接移行したことを確認したか、あるいは受精処理されてから開始される最初の卵割において、前記胚の割球数が2個の状態を経ることなく前記胚の割球数が3個以上の状態に直接移行したか、によって前記胚を選抜する、方法。
It ’s a method of selecting embryos .
An image storage step of chronologically storing images for each well , in which embryos housed and cultured in a plurality of wells provided in a culture container are imaged at set time intervals,
Said reading the image stored in the image storing step, a selection step of selecting a embryo by the analyzing changes over time in the number of blastomeres the embryo in the image,
Equipped with a,
In the selection step, in the first cleavage started after the fertilization process, it was confirmed that the number of blastomeres of the embryo directly shifted to the two state, or the first started after the fertilization process. A method of selecting an embryo according to whether or not the number of blastomeres of the embryo directly shifts to a state of 3 or more without going through the state of 2 blastomeres in the cleavage .
JP2019087392A 2019-05-07 2019-05-07 Embryo selection system Active JP7000379B2 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
JP2019087392A JP7000379B2 (en) 2019-05-07 2019-05-07 Embryo selection system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
JP2019087392A JP7000379B2 (en) 2019-05-07 2019-05-07 Embryo selection system

Related Parent Applications (1)

Application Number Title Priority Date Filing Date
JP2017236640A Division JP6732722B2 (en) 2017-12-11 2017-12-11 Embryo selection system

Publications (3)

Publication Number Publication Date
JP2019141090A JP2019141090A (en) 2019-08-29
JP2019141090A5 true JP2019141090A5 (en) 2021-01-28
JP7000379B2 JP7000379B2 (en) 2022-01-19

Family

ID=67771370

Family Applications (1)

Application Number Title Priority Date Filing Date
JP2019087392A Active JP7000379B2 (en) 2019-05-07 2019-05-07 Embryo selection system

Country Status (1)

Country Link
JP (1) JP7000379B2 (en)

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2010004789A (en) * 2008-06-26 2010-01-14 Nikon Corp Embryo observation apparatus
JP5807288B2 (en) * 2010-06-30 2015-11-10 大日本印刷株式会社 Method for producing embryo by in vitro culture, and method, apparatus, and system for selecting embryo
US10628944B2 (en) * 2014-07-01 2020-04-21 INSERM (Institut National de la Santé et de la Recherche Médicale) Methods for three dimensional reconstruction and determining the quality of an embryo
US10180387B2 (en) * 2014-07-29 2019-01-15 National University Corporation Hamamatsu University School Of Medicine Identification device and identification method
GB2531699A (en) * 2014-10-03 2016-05-04 Unisense Fertilitech As Embryo Assessment
JP6528608B2 (en) * 2015-08-28 2019-06-12 カシオ計算機株式会社 Diagnostic device, learning processing method in diagnostic device, and program
WO2017150194A1 (en) * 2016-03-04 2017-09-08 コニカミノルタ株式会社 Image processing device, image processing method, and program

Similar Documents

Publication Publication Date Title
Kharabian Masouleh et al. Empirical examination of the replicability of associations between brain structure and psychological variables
KR101822404B1 (en) diagnostics system for cell using Deep Neural Network learning
Haft-Javaherian et al. Deep convolutional neural networks for segmenting 3D in vivo multiphoton images of vasculature in Alzheimer disease mouse models
Short et al. Global quantification of tissue dynamics in the developing mouse kidney
Reagh et al. Object and spatial mnemonic interference differentially engage lateral and medial entorhinal cortex in humans
Lahti et al. How precise is egg discrimination in weaverbirds?
Captur et al. Morphogenesis of myocardial trabeculae in the mouse embryo
Cheng et al. Rigid firing sequences undermine spatial memory codes in a neurodegenerative mouse model
Shea Stone tool analysis and human origins research: Some advice from uncle Screwtape
Nicol et al. An ocean observation system for monitoring the affects of climate change on the ecology and sustainability of pelagic fisheries in the Pacific Ocean
Beck et al. Winter associations predict social and extra-pair mating patterns in a wild songbird
Azevedo et al. DRhoGEF2 regulates cellular tension and cell pulsations in the Amnioserosa during Drosophila dorsal closure
Sutherland et al. Shifting white pox aetiologies affecting Acropora palmata in the Florida Keys, 1994–2014
JP2015087903A (en) Apparatus and method for information processing
Welch et al. Integrative inference of brain cell similarities and differences from single-cell genomics
Ganz et al. Image velocimetry and spectral analysis enable quantitative characterization of larval zebrafish gut motility
Ottolini et al. A cautionary note against embryo aneuploidy risk assessment using time-lapse imaging
Wilson et al. Developmental rewiring between cerebellar climbing fibers and Purkinje cells begins with positive feedback synapse addition
Jernigan et al. Toward an integrative science of the developing human mind and brain: focus on the developing cortex
Ruiz-Raya et al. Signal detection and optimal acceptance thresholds in avian brood parasite–host systems: implications for egg rejection
Wagstyl et al. Transcriptional cartography integrates multiscale biology of the human cortex
Welsh et al. Clustered parrotfish feeding scars trigger partial coral mortality of massive Porites colonies on the inshore Great Barrier Reef
Tibbetts et al. Complex signals alter recognition accuracy and conspecific acceptance thresholds
JP2019141090A5 (en)
Abd El Hamid et al. Identifying genetic biomarkers associated to Alzheimer's disease using Support Vector Machine