WO2018070288A1

WO2018070288A1 - Fertilization determination system

Info

Publication number: WO2018070288A1
Application number: PCT/JP2017/035857
Authority: WO
Inventors: 憲隆福永
Original assignee: 憲隆福永
Priority date: 2016-10-11
Filing date: 2017-10-02
Publication date: 2018-04-19
Also published as: JP2018061440A

Abstract

Provided is a fertilization determination system comprising: a culturing unit that cultures an egg that has undergone a fertilization process; an image acquisition unit that acquires a plurality of images by capturing, at set time intervals, images of the state of the egg being cultured by the culturing unit; and a determination unit that determines whether the egg has been fertilized by analyzing the state of the egg captured in the images.

Description

Fertilization determination system

The present invention relates to a fertilization determination system.

In the field of infertility treatment, selection of embryos is performed by evaluating the embryos in culture from the viewpoint of improvement in conception rate and QOL of patients. As a method for non-invasively evaluating an embryo, there is a method for evaluating the developmental state of an embryo through morphological observation with a microscope.

JP 2012-29686 A

In the embryo selection system disclosed in Patent Document 1, embryos are selected using the morphology and oxygen consumption of the embryo as indicators. However, a system for confirming fertilization, which is a premise of embryogenesis, has not been sufficiently considered so far. In addition, the number of specimens that can be confirmed is limited because humans have confirmed each egg, which has been a specimen, at a glance, to see if eggs that have been fertilized by fertilization have been fertilized normally. there were. In order to solve such problems, there has been a demand for a technique for confirming whether a fertilized egg is fertilized and a technology that enables confirmation of fertilization in more specimens than human confirmation. .

The present invention has been made to solve at least a part of the problems described above, and can be realized as the following forms.

(1) According to one aspect of the present invention, a fertilization determination system is provided. The fertilization determination system includes a culture unit that cultures a fertilized egg, and an image acquisition unit that captures a state of the egg cultured by the culture unit at set time intervals and acquires a plurality of images. And a determination unit that determines whether the egg is fertilized by analyzing the state of the egg reflected in the image. If it is set as such an aspect, the determination part can determine whether the egg is fertilizing based on the analysis of the image by which the state of the fertilized egg was image | photographed. For this reason, the system which can confirm whether the fertilized egg is fertilized is provided. In addition, since the specimen egg is mechanically analyzed, more specimens can be confirmed than humans can confirm. Moreover, since it is determined whether the fertilization is performed by the determination unit, it is possible to reduce the complexity of the determination as compared with human eyes.

(2) In the fertilization determination system according to the above aspect, the determination unit determines whether the egg is fertilized by analyzing changes over time of the egg in at least two images acquired at different times. May be. If it is set as such an aspect, the time-dependent change of an egg can be analyzed by analyzing at least 2 image. For this reason, it can be determined whether the egg is fertilized based on the change of the egg over time.

(3) In the fertilization determination system according to the above aspect, the determination unit may learn about the characteristics of the egg shown in the image by supervised learning and determine whether the egg is fertilized based on the learning. . With such an aspect, it can be determined whether the egg is fertilized based on the criterion learned by the determination unit through supervised learning.

(4) In the fertilization determination system according to the above aspect, the determination unit learns about the characteristics of the egg shown in the image by deep learning using a multilayer neural network, and the egg is fertilized based on the learning. It may be determined. If it is set as such an aspect, it can be determined whether the egg is fertilizing based on the reference | standard which the determination part learned by deep learning.

(5) In the fertilization determination system according to the above aspect, the determination unit may include a notification unit that notifies a determination image used for determination among the images. If it is set as such an aspect, the user who uses a fertilization determination system can know which image the determination part determined fertilization.

(6) In the fertilization determination system according to the above aspect, the notification unit may notify the determination image and may notify the determination image in the determination image based on the determination basis. With this aspect, the user using the fertilization determination system can know which image the determination unit uses to determine fertilization, and the determination unit can know the information on which the determination is based. it can.

(7) According to one aspect of the present invention, a method for selecting a non-fertilized egg is provided. This method of selecting non-fertilized eggs is a method of selecting non-fertilized eggs that have not been normally fertilized among fertilized eggs, a culture step of culturing the eggs, and a culture in the culture step. An image acquisition step of acquiring a plurality of images by photographing the state of the eggs being set at a set time interval, and a selection step of selecting the non-fertilized eggs by analyzing the state of the eggs reflected in the images And comprising. According to such an aspect, a non-fertilized egg can be selected based on an analysis of an image in which a fertilized egg is photographed. For this reason, the method of selecting the non-fertilized egg which is not normally fertilized among the eggs which have been fertilized is provided.

The present invention can be realized in various forms other than the fertilization determination system. For example, the present invention can be realized in the form of a fertilization determination device. Further, the present invention is not limited to the above-described embodiments, and it is needless to say that the present invention can be implemented in various forms without departing from the spirit of the present invention.

It is explanatory drawing which shows the structure of the fertilization determination system in 1st Embodiment. It is an example of an image labeled as an egg whose pronucleus has not been confirmed. It is an example of the image labeled as the egg by which one pronucleus was confirmed. It is an example of the image labeled as the egg by which two pronuclei were confirmed. It is an example of the image labeled as the egg by which three pronuclei were confirmed. It is a flow which shows the image acquisition process which a control part performs. It is a flow which shows the fertilization determination process which a control part performs. It is explanatory drawing explaining the learning of the image by deep learning.

A. First embodiment:
FIG. 1 is an explanatory diagram illustrating a configuration of a fertilization determination system 10 according to the first embodiment. The fertilization determination system 10 is a system that determines whether a fertilized human egg is fertilized. The fertilized egg is an egg that has been subjected to fertilization treatment such as a conventional method in which sperm and an egg are co-cultured or a microinsemination method. The fertilization determination system 10 includes a culture unit 110, an image acquisition unit 130, a control unit 140, a user interface 150, and a notification unit 160.

The culture unit 110 is a so-called incubator that cultures fertilized eggs. The culture conditions such as temperature, humidity, oxygen concentration, carbon dioxide concentration, and culture time in the culture unit 110 are controlled by the control unit 140 based on the contents previously input by the user via the user interface 150. The culture unit 110 cultures the eggs in a state where the culture container 200 that is a container for culturing the fertilized egg is fixed in the culture unit 110.

The culture vessel 200 is a well plate having 12 wells in 3 rows and 4 columns. Numbers 1 to 12, which are well numbers, are attached to the bottom of each well of the culture vessel 200. The culture container 200 is a container for putting one egg in each well and culturing.

The culture unit 110 has a container transport unit 115. The container transport unit 115 has a shape extending in the horizontal direction and constitutes a bottom surface portion of the culture unit 110. The container transport part 115 has a fixing part (not shown) for fixing the culture container 200 on the surface facing the upper side in the gravity direction. The culture unit 110 cultivates eggs in a state where the culture container 200 is fixed to the fixed unit.

The container transport unit 115 transports the culture container 200 fixed to the fixed unit by moving the fixed unit to a position below the gravitational direction of the image acquisition unit 130 that partially protrudes inside the culture unit 110. . When the image acquisition by the image acquisition unit 130 is completed, the container transport unit 115 transports the culture container 200 to the initial position. In FIG. 1, the position where the culture vessel 200 is shown is the initial position.

The frequency (time interval) at which the container transport unit 115 transports the culture container 200 is controlled by the control unit 140 based on the contents set in advance by the user via the user interface 150. In the present embodiment, the container transport unit 115 is controlled to transport the culture container 200 to the position below the image acquisition unit 130 in the gravity direction every 15 minutes. The container transport unit 115 adjusts the position of the culture container 200 two-dimensionally in the vertical and horizontal directions as viewed from the image acquisition unit 130 after the culture container 200 is transported to a position below the gravity direction of the image acquisition unit 130. Each well can be arranged at a position where the image acquisition unit 130 can acquire an image. When the image acquisition by the image acquisition unit 130 is completed, the container transport unit 115 transports the culture container 200 to the initial position. The process of acquiring an image of each well in the culture vessel 200 by the image acquisition unit 130 will be described later.

The image acquisition unit 130 acquires images by photographing the state of eggs cultured by the culture unit 110 at set time intervals. In the present embodiment, the image acquisition unit 130 captures a plurality of images for each well in the culture container 200 in a time-series manner by photographing the state of the egg each time the container transport unit 115 transports the culture container 200. To get to. In another embodiment, the image acquisition unit 130 may acquire images by capturing images at time intervals directly instructed by the control unit 140. The position of the well from which the image acquisition unit 130 acquires images among the 12 wells of the culture vessel 200 is designated by the user via the user interface 150 in advance. In the following description, a well position designated by the user is referred to as a “designated position”. In the present embodiment, the image acquisition unit 130 is a CCD camera.

The control unit 140 is constituted by a microcomputer including a central processing unit and a main storage device. The control unit 140 controls each unit of the fertilization determination system 10. In addition, the control unit 140 controls the culture unit 110, the container transport unit 115, and the image acquisition unit 130 based on the contents previously input by the user via the user interface 150.

The control unit 140 includes an image storage unit 142 and a determination unit 144.

The image storage unit 142 stores the image acquired by the image acquisition unit 130. The image storage unit 142 sends the acquired image of each well to the determination unit 144.

The determination unit 144 determines whether the egg is fertilized by analyzing the state of the egg shown in the image sent from the image storage unit 142. In the present embodiment, the determination unit 144 uses the images of each well acquired by the image acquisition unit 130 at a time interval of 15 minutes for 24 hours after the culture unit 110 starts culturing eggs. Determine if is fertilized.

In this embodiment, the determination unit 144 determines whether the egg is fertilized by checking the number of pronuclei in the egg. In a normally fertilized egg, two pronuclei generally appear within 22 hours after fertilization.

In this embodiment, the determination unit 144 determines whether an egg is fertilized by analyzing two images acquired at different times. In the present embodiment, among the images acquired by the image acquisition unit 130, two images acquired at different times are determined as two images that can most significantly recognize the difference in the number of pronuclei in the egg. The unit 144 selects. Only when the two images are two images, one image in which the number of pronuclei in the egg is not confirmed and one image in which two pronuclei in the egg are confirmed, the determination unit 144 Determine that the egg is fertilized. As described above, since the temporal change of the eggs in the two images can be analyzed, it can be determined whether the egg is fertilized based on the temporal change of the eggs. Further, by comparing the difference in the number of pronuclei in two images, fertilization can be determined with higher accuracy than determination using one image.

The determination unit 144 learns about the characteristics of the egg shown in the image by supervised learning, and determines whether the egg is fertilized based on the learning. In the present embodiment, the determination unit 144 learns about the determination of the number of pronuclei in the egg shown in the image, and determines whether the egg is fertilized based on the learning. For this reason, the determination unit 144 can determine whether the egg is fertilized based on the determination criterion for the number of pronuclei learned by supervised learning.

2, FIG. 3, FIG. 4 and FIG. 5 are explanatory diagrams showing examples of images used by the determination unit 144 in supervised learning. FIG. 2 is an example of an image labeled as an egg in which a pronucleus has not been confirmed in the fertilized egg. FIG. 3 is an example of an image labeled as an egg in which one pronucleus has been confirmed in the fertilized egg. FIG. 4 is an example of an image labeled as an egg in which two pronuclei have been confirmed in the fertilized egg. FIG. 5 is an example of an image that is labeled as an egg in which three pronuclei have been confirmed in a fertilized egg. In a fertilized egg, when a pronucleus is not confirmed, it is generally determined to be a non-fertilized egg. In addition, in the fertilized egg, when one or three or more pronuclei are confirmed, it is generally determined that the egg is abnormally fertilized.

The user interface 150 exchanges information with the user of the fertilization determination system 10. In the present embodiment, the user interface 150 is a touch panel that displays an image and receives an instruction input from the user on the image. In another embodiment, the user interface 150 may include a push button that receives an instruction input from the user.

The alerting | reporting part 160 alert | reports the determination image used for determination among images. The notification unit 160 notifies the determination image when the user is viewing the determination result by the determination unit 144 on the touch panel screen as the user interface 150. For this reason, the user who uses the fertilization determination system 10 can know which image the determination unit 144 has determined fertilization. In this embodiment, since the time acquired for each acquired image is attached to the image, the user can know when the egg is fertilized by checking the time attached to the determination image. it can.

In addition, the notification unit 160 notifies the determination image 144 of information used as a basis for determination in the determination image. When the user is browsing the notified determination image on the screen of the touch panel that is the user interface 150, the notification unit 160 notifies the determination unit 144 of information that is the basis for the determination. In this embodiment, the alerting | reporting part 160 alert | reports the positional information about the part which the determination part 144 recognized as a pronucleus in the determination image.

FIG. 6 is a flow showing an image acquisition process executed by the control unit 140. The control unit 140 executes an image acquisition process when the culture vessel 200 is transported to a position below the image acquisition unit 130 in the direction of gravity.

When the image acquisition process is started, the control unit 140 calculates a variable A representing the number of wells designated by the user (step S100). After calculating the variable A indicating the number of designated wells (step S100), the control unit 140 obtains an image of the well with the smallest number among wells that have been designated and have not been photographed. The acquisition unit 130 is caused to photograph (step S110). The numbers are 1 to 12 well numbers given to the bottom of each well.

In step S110, the image acquisition unit 130 acquires a well image in the following steps (1) and (2). (1) The control unit 140 causes the container transport unit 115 to adjust the position of the culture vessel 200 two-dimensionally, and moves the position of the well to a position where the image acquisition unit 130 can perform imaging. (2) The control unit 140 moves the well to a position where the image acquisition unit 130 can perform imaging, and then causes the image acquisition unit 130 to perform imaging.

After an image of the well with the smallest number among the designated wells that have not been shot, the control unit 140 stores the number of the well that has been shot (step S110). S120). After storing the number of the well for which imaging has been completed (step S120), the control unit 140 decrements the variable A. (Step S130).

After the variable A is decremented (step S130), the control unit 140 determines whether the variable A has become 0 (step S140). When the variable A becomes 0 (step S140: YES), the control unit 140 ends the image acquisition process of FIG.

When the variable A is not 0 (step S140: NO), the control unit 140 returns to step S110 and repeats the processing of steps S110 to S140 until the variable A becomes 0. When the variable A becomes 0 (step S140: YES), the control unit 140 ends the image acquisition process of FIG.

FIG. 7 is a flow showing fertilization determination processing executed by the control unit 140. The control unit 140 executes fertilization determination processing when 7 hours have elapsed since the start of egg culture. In addition, the control unit 140 repeatedly executes the fertilization determination process every hour from 7 hours to 24 hours after the start of egg culture.

When the fertilization determination process is started, the control unit 140 calculates a variable A representing the number of wells designated by the user (step S200). After calculating the variable A representing the number of designated wells (step S200), the control unit 140 extracts an image of the well with the smallest number among the designated wells that have not been determined. (Step S210). In the present embodiment, for example, in the fertilization determination process that is executed when 7 hours have elapsed since the start of the egg culture, the image of the designated well is displayed after the culture unit 110 starts the egg culture. Since it is acquired by the image acquisition unit 130 at a time interval of 15 minutes during 7 hours, there are 28 images for each designated well. That is, in the fertilization determination process that is executed when 7 hours have passed since the start of the egg culture, in step S210, the control unit 140 controls 28 pieces of one of the designated wells. Extract images. In the fertilization determination process executed when 24 hours have elapsed since the start of egg culture, the control unit 140 extracts 96 images for one of the designated wells.

After extracting the image of the well with the smallest number among the designated wells that have not been determined (step S210), the control unit 140 determines the pronucleus in the egg in the extracted image. Two images that can recognize the difference in number most remarkably are selected (step S220).

After selecting the two images that can recognize the difference in the number of pronuclei in the egg most remarkably from the extracted images (step S220), the determination unit 144 in the control unit 140 compares the two images. It is determined whether fertilization is performed (step S230).

After comparing the two images to determine whether fertilization is performed (step S230), the control unit 140 stores the number of the well for which determination has been completed (step S240). After storing the number of the well for which the determination has been completed (step S240), the control unit 140 decrements the variable A. (Step S250).

After the variable A is decremented (step S250), the control unit 140 determines whether the variable A has become 0 (step S260). When the variable A becomes 0 (step S260: YES), the control unit 140 ends the fertilization determination process of FIG.

If the variable A is not 0 (step S260: NO), the control unit 140 returns to step S210 and repeats the processing of steps S210 to S260 until the variable A becomes 0. When the variable A becomes 0 (step S260: YES), the control unit 140 ends the fertilization determination process of FIG.

According to the embodiment described above, the determination unit 144 can determine whether or not the egg is fertilized based on the analysis of the image in which the state of the fertilized egg is photographed. For this reason, the system which can confirm fertilization of the fertilized egg is provided. In addition, since the fertilized eggs as specimens are mechanically analyzed, more specimens can be confirmed than humans can confirm. Moreover, since it is determined by the determination part 144 whether it is fertilizing, the complexity of determination can be reduced compared with human checking with eyes.

B. Second embodiment:
The configuration of the fertilization determination system in the second embodiment is the same as the configuration of the fertilization determination system 10 in the first embodiment, except that a determination unit that performs learning different from the determination unit 144 in the first embodiment is provided.

The determination unit in the second embodiment learns about the characteristics (number of pronuclei) of an egg shown in the image by deep learning using the deep neural network 400 that is a multilayer neural network, and the egg is fertilized based on the learning. Judge whether you are doing. For this reason, it can be determined whether the egg is fertilized based on the criterion learned by the determination unit through deep learning. When the feature amount of a normally fertilized egg extracted by deep learning is a feature amount that cannot be recognized by a human, fertilization confirmation of the egg can be performed with higher accuracy than that performed by a human.

FIG. 8 is an explanatory diagram explaining image learning by deep learning. The deep neural network 400 is a network that models a learning mechanism in the human brain nervous system. The deep neural network 400 includes an input layer 410, a plurality of intermediate layers 420, and an output layer 430. The deep neural network 400 according to the second embodiment includes four intermediate layers 420.

The input layer 410 is a layer into which information is input. The intermediate layer 420 is a layer that calculates a feature amount based on information transmitted from the input layer 410. The output layer 430 is a layer that outputs a result based on information transmitted from the intermediate layer 420.

An image 300 in FIG. 8 is an image showing an egg that has been fertilized. In the image 300, an image labeled as an egg in which no pronuclei have been confirmed, an image labeled as an egg in which one pronucleus has been confirmed, and an egg in which two pronuclei have been confirmed. An image labeled as being, an image labeled as being an egg in which three pronuclei have been confirmed, and the like are included.

The learning method using the deep neural network 400 will be described. When the image 300 labeled with the number of pronuclei is input, the input layer 410 transmits the information to the intermediate layer 420. The intermediate layer 420 calculates the feature value of the pronucleus based on the information transmitted from the input layer 410. The output layer 430 outputs the feature amount of the pronuclei calculated based on information transmitted from the intermediate layer. The determination part in 2nd Embodiment determines whether the egg is fertilized on the basis of the output feature-value.

C. Third embodiment:
In the third embodiment, a method for selecting non-fertilized eggs that have not been normally fertilized among the fertilized eggs will be described. This method of selecting a non-fertilized egg includes a culture process, an image acquisition process, and a selection process. The term “non-fertilized egg” as used herein includes a non-fertilized egg that is an egg whose pronucleus have not been confirmed, and an abnormally fertilized egg that is an egg whose one or more pronuclei have been confirmed.

The culture process is a process of culturing the fertilized egg. The image acquisition process is a process of acquiring a plurality of images by photographing the state of the eggs cultured in the culture process at set time intervals. The selection step is a step of selecting a non-fertilized egg by analyzing the state of the egg shown in the image.

According to the third embodiment described above, it is possible to select a non-fertilized egg based on an analysis of an image in which the state of the fertilized egg is photographed. For this reason, the method of selecting the non-fertilized egg which is not normally fertilized among the eggs which have been fertilized is provided.

D. Variation:
In 1st Embodiment, the fertilization determination system 10 was provided with the container conveyance part 115, However, This invention is not limited to this. For example, the fertilization determination system in another embodiment may not include the container transport unit 115. In this case, the image acquisition unit 130 may be provided on the upper side in the gravity direction of the culture vessel 200 fixed to the fixing unit, or the image acquisition unit 130 is configured to be movable on the upper side in the gravity direction of the culture vessel 200. Just do it.

In the first embodiment, the image acquired by the image acquisition unit 130 is stored in the image storage unit 142, but the present invention is not limited to this. For example, the image acquired by the image acquisition unit 130 may be stored on a so-called cloud. In this case, the determination unit 144 acquires an image from the cloud and performs determination.

In the first embodiment, the determination unit 144 determines whether an egg is fertilized by analyzing two images acquired at different times, but the present invention is not limited to this. For example, the determination unit 144 may determine whether the egg is fertilized by analyzing one image in which the number of pronuclei in the egg (selected by the control unit 140) can be recognized most frequently. In this case, for example, the determination unit 144 determines that the egg is fertilized when one image selected by the control unit 140 is an image in which two pronuclei are confirmed.

Further, the determination unit 144 may determine whether the egg is fertilized by analyzing three images acquired at different times (selected by the control unit 140). In this case, the determination unit 144, for example, one image in which the number of pronuclei in the egg is not confirmed, one image in which one pronucleus in the egg is confirmed, and an image in which two pronuclei in the egg are confirmed. It is determined that the egg is fertilized only when three of them are confirmed. The determination unit 144 may determine whether the egg is fertilized by analyzing four or more images acquired at different times (selected by the control unit 140). In this case, for example, the determination unit 144 arranges four or more images in time series, and the egg is fertilized only when the number of pronuclei increases or decreases in the order of 0, 1, 2, and 0. It is determined that

In the third embodiment, the input image 300 is an image labeled with respect to the number of pronuclei, but the present invention is not limited to this. For example, the input image may be an image labeled as fertilized and an image labeled as not fertilized.

The present invention is not limited to the above-described embodiments, examples, and modifications, and can be realized with various configurations without departing from the spirit of the invention. For example, the technical features in the embodiments, examples, and modifications corresponding to the technical features in each embodiment described in the summary section of the invention are to solve some or all of the above-described problems, or In order to achieve part or all of the above-described effects, replacement or combination can be performed as appropriate. Further, if the technical feature is not described as essential in the present specification, it can be deleted as appropriate.

DESCRIPTION OF SYMBOLS 10 ... Fertilization determination system 110 ... Culture | cultivation part 115 ... Container conveyance part 130 ... Image acquisition part 140 ... Control part 142 ... Image storage part 144 ... Determination part 150 ... User interface 160 ... Notification part 200 ... Culture container 300 ... Image 400 ... Deep Neural network 410 ... input layer 420 ... intermediate layer 430 ... output layer

Claims

A fertilization determination system,
A culture unit for culturing the fertilized egg;
An image acquisition unit that captures the state of the egg being cultured by the culture unit at a set time interval and acquires a plurality of images;
A determination unit for determining whether the egg is fertilized by analyzing the state of the egg in the image;
A fertilization determination system.
The fertilization determination system according to claim 1,
The fertilization determination system, wherein the determination unit determines whether the egg is fertilized by analyzing a change with time of the egg in at least two images acquired at different times.
The fertilization determination system according to claim 1 or 2,
The fertilization determination system, wherein the determination unit learns about the characteristics of the egg reflected in the image by supervised learning and determines whether the egg is fertilized based on the learning.
The fertilization determination system according to claim 1,
The fertilization determination system, wherein the determination unit learns about the characteristics of the egg reflected in the image by deep learning using a multilayer neural network, and determines whether the egg is fertilized based on the learning.
A fertilization determination system according to any one of claims 1 to 4,
The determination unit is a fertilization determination system including a notification unit that notifies a determination image used for determination among the images.
The fertilization determination system according to claim 5,
The fertility determination system, in which the notification unit notifies the determination image and notifies the determination image of information used as a basis for determination in the determination image.
A method of selecting non-fertilized eggs that have not been normally fertilized among fertilized eggs,
A culture step of culturing the egg;
An image acquisition step of acquiring a plurality of images by photographing the state of the eggs cultured in the culture step at set time intervals;
A selection step of selecting the non-fertilized eggs by analyzing the state of the eggs in the image;
A method for selecting a non-fertilized egg.