Patent Description:
The present disclosure relates to a method for analysis of yeast.

From ancient times to the present, yeast have been closely related to human life. And the yeast have been widely used in food production, wine brewing, scientific research, and other fields. Based on the demand of modern industrial production and quality control, accurately counting of the yeast has become a more and more important link. <CIT> discloses the counting systems with microscope or magnifying glass based on image analysis that carry out an automatic, semi-automatic or semi-assisted counting. <CIT> discloses a non-contact microscopic measurement auxiliary device and its measurement method. <CIT> discloses an information management device for a mass spectrometer which is suitable for managing information relating to a mass spectrometer that employs a matrix-assisted laser desorption/ionization method, a laser desorption/ionization method or similar ionization method. <CIT> discloses automated systems for analysing air samples for the presence of respirable fibres such as asbestos fibres or synthetic mineral fibres (SMF). <CIT> discloses a testing apparatus for performing an assay.

Other features of the present disclosure and advantages thereof may become apparent from the following detailed description of examples of the present disclosure with reference to the drawings.

The drawings forming a portion of the present disclosure describe examples of the present disclosure and are used together with the present disclosure to explain the principles of the present disclosure.

Referring to the drawings, the present disclosure may be more clearly understood according to the following detailed description, wherein:.

It should be noted that in some examples described below, the same number is used between different drawings to indicate the same part or a part with the same function, and the repeated description thereof is omitted. In the present disclosure, similar labels and letters are used to indicate similar items. Therefore, once an item is defined in a drawing, a further discussion may not need to be described in subsequent drawings.

In order to facilitate understanding, position, size, range of each structure shown in the drawings or the like may not indicate the actual position, size, or range in some cases. Therefore, the present disclosure is not limited to the position, dimension, ranges disclosed in the drawings, or the like.

The examples of the present disclosure are described in detail with reference to the drawings. It should be noted that unless stated otherwise or obvious from the context, the relative arrangement of components and steps, numerical expressions, and values set forth in these embodiments do not limit the scope of the present disclosure.

The following description of at least one example is merely illustrative in nature and is in no way intended to limit the present disclosure and its application or use.

In all the examples shown and discussed in the present disclosure, any specific value should be interpreted as merely for example, and not as a limitation. Therefore, other examples may have different values.

<FIG> is a schematic diagram illustrating a microscopic device according to some examples of the present disclosure.

As shown in <FIG>, the microscopic device <NUM> may include an image sensor <NUM>, a memory <NUM>, a processor <NUM>, an optical imaging device <NUM>, a sample table <NUM>, and a light source <NUM>. During an operation, a sample plate may be arranged on the sample table <NUM>. The light source <NUM> may emit light towards the sample plate. The optical imaging device <NUM> may include, for example, an objective and an eyepiece (not shown). Each of the objective and the eyepiece may be composed of one or more sets of lenses. An optical image generated by the optical device <NUM> may be received by the image sensor <NUM> and converted into a digital image by the image sensor <NUM>. The image sensor may be, for example, a charge-coupled device (CCD), a complementary metal-oxide semiconductor (CMOS), or the like. In some examples according to the present disclosure, an image capturing device such as a mobile phone, or a camera may also be arranged in an optical path. The image capturing device may also include image sensors, and may capture an image of a sample in the sample plate through the optical device <NUM>.

The digital image captured by the image sensor <NUM> may be stored in the memory <NUM>, and the processor <NUM> may read and process the digital image in the memory <NUM>.

<FIG> is a schematic diagram illustrating a sample plate according to some examples of the present disclosure. As shown in <FIG>, a sample plate <NUM> may include a plurality of sample cells <NUM> in which samples may be accommodated. In addition, the sample plate <NUM> may also include a scaling pattern <NUM>.

In <FIG>, the scaling pattern <NUM> is located at the bottom of a sample cell (i.e., on the surface where the sample cell contacts the sample). When capturing an image of a sample by the microscope device <NUM>, the optical imaging device <NUM> may focus on the bottom of the sample cell, and set the scaling pattern <NUM> at the bottom of the sample cell to capture a clear image of the scaling pattern while capturing the sample image. The scaling pattern <NUM> may be a line segment along a horizontal direction with a length of L. For example, in some examples,.

L may be <NUM>-<NUM>. Using the scaling pattern <NUM>, the magnification of the microscopic device <NUM> may be accurately obtained.

For example, as shown in <FIG>, for the image sensor <NUM> whose pixels are evenly arranged in two directions perpendicular to each other (the X direction and the Y direction), if coordinates at both ends of the line segment of the scaling pattern <NUM> are (x1, y1) and (x2, y2) in the digital image generated by the image sensor <NUM>, respectively. Then, the coordinates (x1, y1) and (x2, y2) represent positions of the pixels corresponding to both ends of the line segment on the image sensor <NUM>. Then, a size k of an image of the line segment generated by the line segment on the sample plate on the image sensor <NUM> may be determined based on a formula (<NUM>): <MAT> where D represents spacing between adjacent pixels in the image sensor <NUM>, that is, a distance from a center of a pixel to a center of an adjacent pixel of the pixel along the X direction or Y direction. The function "sqrt" represents determining a square root.

Then, a magnification M of the optical imaging device <NUM> of the microscope device <NUM> may be determined based on the following formula (<NUM>): <MAT>.

In the above method, an actual magnification of the microscopic device <NUM> may be accurately obtained.

In the above example, a pixel array of the image sensor <NUM> may be a rectangular array, and the spacing of the adjacent pixels may be the same in the X direction and the Y direction. In other embodiments according to the present disclosure, the spacing between the adjacent pixels of the image sensor <NUM> may be different in the X direction and the Y direction. For example, if the spacing between the adjacent pixels along the X direction is D1 and the spacing between adjacent pixels along the Y direction is D2, the size k of the image of the line segment generated by the line segment on the sample plate on the image sensor <NUM> may be determined based on the following formula (<NUM>): <MAT>.

Then, the actual magnification M of the microscopic device <NUM> may be accurately obtained.

The above operation of determining the actual magnification may be performed by, for example, the processor <NUM> of the microscope device <NUM>. For example, the spacing between adjacent pixels of the image sensor <NUM> may be stored in the memory <NUM> in advance. When the image sensor <NUM> generates a digital image of the sample plate <NUM>, the digital image may be stored in the memory <NUM>.

Then, the processor <NUM> may read the digital image from the memory <NUM> and recognize the scaling pattern in the digital image. Next, the processor <NUM> may read the spacing between adjacent pixels of the image sensor <NUM> from the memory and determine the actual magnification M of the microscopic device <NUM> based on the above formulas (<NUM>)-(<NUM>).

In addition, in some examples according to the present disclosure, for the sample plate <NUM> with a plurality of sample cells <NUM>, the magnification M may also be determined using the following method.

For the sample plate <NUM> shown in <FIG> with three sample cells <NUM>, the corresponding magnifications M1, M2, and M3 may be determined respectively based on the scaling pattern <NUM> on each of the sample cells <NUM>, and then the actual magnification M of the microscopic device may be calculated by a formula (<NUM>): <MAT>.

That is, an average value of the magnifications M1, M2, and M3 are designated as the actual magnification M of the microscopic device. In this way, the calculation error may be reduced and the accuracy of magnification may be further improved.

In addition, in other examples according to the present disclosure, a sum K' of the line segments of each scaling pattern <NUM> may be determined based on the following formula (<NUM>): <MAT> where (x1, y1) and (x2, y2) are the coordinates of both ends of the line segment of the scaling pattern of a first sample cell <NUM> in the upper of <FIG> in the digital image; (x3, y3) and (x4, y4) are the coordinates of both ends of the line segment of the scaling pattern of a second sample cell <NUM> in the upper of <FIG> in the digital image, (x5, y5) and (x6, y6) are the coordinates of both ends of the line segment of the scaling pattern of a third sample cell <NUM> in the lower of <FIG> in the digital image.

Then, the actual magnification M of the microscopic device may be determined based on a formula (<NUM>): <MAT>.

In this way, the calculation error may be reduced and the accuracy of magnification may be further improved.

The above examples briefly describe how to determine the actual magnification of the microscopic device <NUM> based on the scaling pattern on the sample plate. It should be understood that the present disclosure is not limited to the above methods. Under the instruction and enlightenment of the present disclosure, those skilled in the art may also adopt other ways to determine the actual magnification of the microscopic device <NUM> based on the scaling pattern.

<FIG> is another schematic diagram illustrating an sample plate according to some examples of the present disclosure. As shown in <FIG>, a sample plate <NUM> may include a plurality of sample cells <NUM> in which samples to be observed and captured may be accommodated. In addition, the sample plate <NUM> also has a scaling pattern <NUM>.

In <FIG>, the scaling pattern <NUM> may be located at the bottom of the sample cell. The scaling pattern <NUM> may be tick marks arranged at an equal interval, each tick mark may extend along the horizontal direction (a first direction), and spacing of the tick marks in the vertical direction (a second direction) is D. In some embodiments according to the present disclosure, the spacing D may be, for example, <NUM> -<NUM>. The magnification of the microscopic device may be accurately determined based on the scaling pattern <NUM>.

For example, based on the digital image generated by the image sensor <NUM>, the processor <NUM> may obtain a coordinate (x1', y1') of a point on a tick mark in the scaling pattern <NUM> and a coordinate (x2', y2') of an intersection point of a line along the direction vertical to the tick mark and passing through point (x1', y1') and an adjacent tick mark.

Using a method similar to the method described above, the actual magnification of the microscopic device <NUM> may be determined.

In the example shown in <FIG>, a plurality of tick marks <NUM> may be arranged on each sample cell. When the magnification of the microscopic device <NUM> is relatively large, the actual magnification may be accurately determined even if only a portion of a sample cell is included in the visual field.

<FIG> is another schematic diagram illustrating a sample plate <NUM> according to some embodiments of the present disclosure. As shown in <FIG>, in the sample plate <NUM>, the scaling pattern <NUM> may be arranged outside a sample cell <NUM>. In this way, interference of the scaling pattern <NUM> on the sample in the sample cell <NUM> may be avoided, and a sample may be more clearly observed and analyzed. In order to capture a clear image of the scaling pattern <NUM>, the scaling pattern <NUM> may be located on the same plane as the bottom of the sample cell.

<FIG> is another schematic diagram illustrating a sample plate <NUM> according to some examples of the present disclosure. As shown in <FIG>, a sample plate <NUM> may include a plurality of sample cells <NUM>. A cross-shaped scaling pattern <NUM> may be arranged at the bottom of each of the sample cells <NUM>. The scaling pattern <NUM> may include two line segments perpendicular to each other, and lengths of the two line segments may be the same or different.

Using the scaling pattern <NUM> on the sample plate <NUM> of <FIG>, the magnification of the microscopic device may also be determined from the digital image generated by the image sensor <NUM>. For example, the magnification of the microscopic device may be determined based on the above formulas (<NUM>)-(<NUM>) and the length of any one of the two line segments in the scaling pattern <NUM>. Alternatively, two magnifications may be determined respectively based on each of the two line segments, and then an average value of the two magnifications may be designated as the magnification of the microscopic device.

In addition, the scaling pattern <NUM> on the sample plate <NUM> of <FIG> may also be used for identifying and correcting a distortion of the microscopic device <NUM>. For example, when there is no distortion in the optical imaging device <NUM> of the microscope device <NUM>, an image of the scaling pattern <NUM> should also be two line segments perpendicular to each other, as shown in <FIG>. However, if there is a distortion in the optical imaging device <NUM> of the microscope device <NUM>, the two line segments in the image of the scaling pattern <NUM> may no longer be vertical, as shown in <FIG>. Based on the image of the two line segments, the processor <NUM> may recognize the distortion of the optical imaging device of the microscope device <NUM>. Further, the processor <NUM> may also correct the digital image generated by the image sensor <NUM> based on known parameters such as a size of the scaling pattern <NUM>, to improve the image quality.

The sample plate according to the present disclosure and how to obtain the magnification of the microscopic device based on the scaling pattern on the sample plate are described above. It should be understood that the present disclosure may not be limited to the above embodiments.

For example, <FIG> is another schematic diagram illustrating a sample plate <NUM> according to some examples of the present disclosure. As shown in <FIG>, the sample plate <NUM> may include a plurality of sample cells <NUM> extending in a horizontal direction, and a scaling pattern <NUM> may be arranged at the bottom of each of the sample cells <NUM>. The scaling pattern <NUM> may include a plurality of tick marks, each of the plurality of tick marks may extend in a horizontal direction (a first direction), and the plurality of tick marks may be arranged in the direction of a dotted line <NUM> (a second direction). The direction of the dotted line <NUM> is not a vertical direction perpendicular to the horizontal direction. In this way, the scaling pattern <NUM> may cover most of the area of the plurality of sample cells <NUM>. When the magnification of the microscopic device <NUM> is large and the visual field may cover only a portion of the plurality of sample cells <NUM>, this form of the scaling pattern <NUM> may ensure that at least one complete tick mark appears in the visual field. In this way, the magnification of the microscopic device may be accurately determined no matter where the sample is observed in the plurality of sample cells <NUM>.

In addition, in some examples according to the present disclosure, the orientation of the sample plate and the plurality of sample cells may also be determined according to the scaling pattern on the sample plate. For example, the sample plate <NUM> shown in <FIG> may include a plurality of sample cells <NUM> arranged in a vertical direction, and each sample cell <NUM> may extend in a horizontal direction.

When observing and photographing samples in the plurality of sample cells <NUM> through the microscope device <NUM>, it may be impossible to observe and photograph all the samples in the plurality of sample cells <NUM> at the same time due to the visual field and other reasons. Therefore, it is necessary to move the sample table <NUM> so that the sample plate is moved in the visual field, to observe and photograph different sample cells <NUM> on the sample plate <NUM> or different portions of the same sample cell <NUM>.

As shown in <FIG>, each tick mark in the scaling pattern <NUM> may extend in the horizontal direction, that is, an extension direction of a tick mark may be the same as the arrangement direction of the sample cell, and the arrangement directions of the plurality of tick marks may be the same as the arrangement directions of the plurality of sample cells. Therefore, although only a portion of the plurality of sample cells may be displayed in the visual field or the image captured by the microscopic device, to perform an operation of observing and photographing different sample cells <NUM> or different areas of the same sample cell <NUM>, the processor <NUM> or the operator may determine the extension directions and arrangement directions of the plurality of sample cells based on the extension directions and arrangement directions of the plurality of the tick marks, and move the sample plate <NUM> on the sample table <NUM> based on the determined extension directions and arrangement directions of the plurality of sample cells.

<FIG> is another schematic diagram illustrating a sample plate <NUM> according to some examples of the present disclosure. As shown in <FIG>, the sample plate <NUM> may include a plurality of sample cells <NUM> extending in the horizontal direction, and the plurality of sample cells <NUM> may be arranged in the vertical direction. A scaling pattern <NUM> may be arranged at the bottom of each of the plurality of sample cells <NUM>.

The scaling pattern <NUM> may include a first mark for determining an arrangement direction and an extension direction of a sample cell <NUM>. The first mark may be composed of two arrows <NUM> and <NUM> perpendicular to each other, wherein the arrow <NUM> may extend in the vertical direction and the arrow <NUM> may extend in the horizontal direction. In addition, in the example, the longer arrow may indicate the arrangement direction of the sample cell, and the shorter arrow may indicate the extension direction of the sample cell. As shown in <FIG>, a length of the arrow <NUM> may be greater than a length of the arrow <NUM>. Therefore, a plurality of sample cells <NUM> being arranged in the vertical direction may be determined based on the extension direction of the arrow <NUM>, and the sample cell <NUM> extending in the horizontal direction may be determined based on the extension direction of the arrow <NUM>.

<FIG> is another schematic diagram illustrating a sample plate <NUM> according to some examples of the present disclosure. As shown in <FIG>, the sample plate <NUM> may include a plurality of sample cells <NUM> arranged in the horizontal direction, and each of the plurality of sample cells <NUM> may extend in the horizontal direction. A scaling pattern <NUM> may be arranged at the bottom of each sample cell <NUM>. The scaling pattern <NUM> may include a first mark for determining an arrangement direction and an extension direction of a sample cell <NUM>. The first mark may be composed of arrows <NUM> and <NUM>, wherein the longer arrow <NUM> may indicate the arrangement direction of the sample cell <NUM>, and the shorter arrow <NUM> may indicate the extension direction of the sample cell <NUM>. In this way, through the extension direction of arrows <NUM> and <NUM>, the plurality of sample cells <NUM> arranged in the horizontal direction may be determined, and each sample cell <NUM> extending in the horizontal direction may also be determined.

<FIG> is another schematic diagram illustrating a sample plate <NUM> according to some examples of the present disclosure. As shown in <FIG>, the sample plate <NUM> includes a plurality of sample cells <NUM> arranged in a vertical direction, and each of the plurality of the sample cells <NUM> may extend in the horizontal direction. A scaling pattern <NUM> is arranged at the bottom of a sample cell <NUM>. The scaling pattern <NUM> includes a second mark <NUM> for identifying the sample plate and a third mark <NUM> for identifying the sample cell. The second mark <NUM> and the third mark <NUM> may be composed of a plurality of tick marks, which may be arranged in the horizontal direction, and each of the plurality of the tick marks may extend in the vertical direction. The leftmost tick mark <NUM> and the rightmost tick mark <NUM> may represent a beginning and an end of the second mark <NUM> and the third identification <NUM>. The second mark <NUM> and the third mark <NUM> may be between the tick mark <NUM> and the tick mark <NUM>. A serial number of the sample plate and a serial number of the sample cell are determined respectively based on the second mark <NUM> and the third mark <NUM>.

As shown in <FIG>, in the lower sample cell <NUM>, the third mark <NUM> includes two tick marks, and the serial number of the sample cell where the third mark <NUM> is located is determined as <NUM>. In the upper sample cell <NUM>, the third mark <NUM> includes a tick mark, and based on spacing between the tick marks, a tick mark is missed in front of this tick mark. Therefore, the serial number of the sample cell where the third mark <NUM> is located may be determined as <NUM>. Similarly, for the third mark <NUM> in the middle sample cell <NUM>, the serial number of the sample cell may be determined as <NUM>.

Similarly, in the second mark <NUM>, based on the spacing between the tick marks, a missing tick mark may represent <NUM>, and then the serial number of the sample plate <NUM> may be determined as <NUM>.

In addition, in some examples of the present disclosure, other ways may also be used to represent a number <NUM> or <NUM>. For example, in a set of tick marks as shown in <FIG>, <NUM> and <FIG> may be represented by tick marks of different lengths. The longer tick mark may represent <NUM> and the shorter tick mark may represent <NUM>. The set of tick marks in <FIG> may be determined as <NUM>.

It should be understood that under the instruction and enlightenment of the present disclosure, those skilled in the art may combine the first mark, the second mark, the third mark, and the tick mark in other ways as a scaling pattern.

<FIG> is a flowchart illustrating a process for operating the microscopic device <NUM> according to some examples of the present disclosure.

As shown in <FIG>, the sample plate may be placed on the sample table <NUM> (operation <NUM>). Samples to be observed and captured may be located in the sample cells of the sample plate.

Then, a digital image of the samples may be generated by the image sensor <NUM> (operation <NUM>). The optical image generated by the optical imaging device <NUM> of the microscopic device <NUM> may be received by the image sensor <NUM> and the digital image may be generated. The digital image may be stored in the memory <NUM>.

Then, the processor <NUM> may read the digital image from the memory <NUM> and perform various processes (operation <NUM>). For example, as described above, based on the scaling pattern in the digital image, the magnification of the microscopic device <NUM> may be determined; the extension direction and arrangement direction of the sample cell may be determined; the (serial number of) sample plate may be determined; or the (serial number of) sample cell may be determined, or the like.

<FIG> is another schematic diagram illustrating a microscopic device according to some examples of the present disclosure. As shown in <FIG>, a microscopic device <NUM> may be an optical microscopic device, including an image sensor <NUM>, a memory <NUM>, a transmission device <NUM>, an inputting device <NUM>, an optical imaging device <NUM>, a sample table <NUM>, and a light source <NUM>. The image sensor <NUM>, the optical imaging device <NUM>, the sample table <NUM>, and the light source <NUM> may be similar to the corresponding devices in the microscopic device <NUM> shown in <FIG>, so a detailed description may not be repeated herein.

The sample plate with the scaling pattern may be arranged on the sample table <NUM>, and the optical imaging device <NUM> generates an optical image of samples. In addition, the scaling pattern in the sample plate is included in the optical image. As described above, the scaling pattern is configured to determine the magnification of the microscopic device, determine the direction of the sample plate, identify the sample plate or sample cell, or the like. The image sensor <NUM> converts an optical image into a digital image.

In addition, a user of the microscope device <NUM> may input information about the scaling pattern (i.e., pattern information) by the inputting device <NUM>. The pattern information may include size information of the scaling pattern. For example, when the scaling pattern is the scaling pattern <NUM> shown in <FIG>, the pattern information may include information about the length L of the line segment. When the scaling pattern is the scaling pattern <NUM> shown in <FIG>, the pattern information may include the information of the spacing D of the tick mark.

In addition, the pattern information may include an identifier of the scaling pattern. For example, the user may input a unique serial number of the scaling pattern by the inputting device <NUM>. The serial number of the scaling pattern is stored in a database in association with relevant information of the scaling pattern. Based on the serial number, the scaling pattern corresponding to the serial number and the relevant information of the scaling pattern, such as size, spacing, etc., are found in the database.

A type of the sample plate is determined by the unique serial number of the scaling pattern. In the database, the serial number of the scaling pattern is stored in association with relevant parameters of the sample plate. The relevant parameters of the sample plate includes: the type of the sample plate, the numbers of sample cells, the depth of sample cells, or the like.

In addition, the user may also input information about the sample (first sample information) by the inputting device <NUM>. For example, the information may include the type of sample. In this way, based on the information about the sample, the type of the samples such as red blood cells, yeast, algae, etc., may be determined.

The transmission device <NUM> may transmit the digital image to other devices. The transmission device <NUM> transmits the digital image toa cloud server. The server may include an image processing device to further process the received image.

<FIG> is another schematic diagram illustrating a microscopic device according to some examples of the present disclosure. As shown in <FIG>, the microscopic device <NUM> may include an image sensor <NUM>, a memory <NUM>, a transmission device <NUM>, an inputting device <NUM>, an optical imaging device <NUM>, a sample table <NUM>, and a light source <NUM>. These components are similar to the corresponding components of the microscopic device <NUM> shown in <FIG>, and may not be repeated herein. In addition, as shown in <FIG>, the microscopic device <NUM> may also include a controller <NUM> and a receiving device <NUM>. The receiving device <NUM> may receive information transmitted by external devices, and the controller <NUM> may control the operation of the microscopic device <NUM> based on the information. In some embodiments according to the present disclosure, the user may interact with the microscopic device <NUM> by a mobile device (e.g., a mobile phone, tablet, laptop, etc.). For example, the microscopic device <NUM> may transmit a captured microscopic image to the mobile device and display the microscopic image on the mobile device. The user may adjust a photographing parameter (such as magnification, observation area, etc.) of the microscopic device <NUM> based on a captured microscopic image, and transmit the photographing parameter to the microscopic device <NUM> by the mobile device. Then, the microscopic device <NUM> may adjust based on the photographing parameter included in the information transmitted by the mobile device, re-capture the microscopic image, and transmit the new microscopic image to the mobile device.

In addition, an interaction between the microscopic device <NUM> and the mobile device may be carried out directly or indirectly through, for example, a cloud server, which may not be limited by the present disclosure.

<FIG> is a schematic diagram illustrating an image processing device according to some examples of the present disclosure. As shown in <FIG>, an image processing device <NUM> may include a receiving device <NUM>, a storage device <NUM>, a processor <NUM>, and a transmission device <NUM>.

The receiving device <NUM> may receive a digital image captured by the above-mentioned microscopic device according to the present disclosure. A scaling pattern may be included in the digital image.

In addition, in some examples according to the present disclosure, the receiving device <NUM> may also receive pattern information and/or first sample information related to the digital image.

The storage device <NUM> may store the digital image and various information received by the receiving device <NUM>.

The processor <NUM> may obtain the digital image and various information from the storage device <NUM> and process the digital image. For example, the processor <NUM> may determine the magnification of the microscopic device based on the scaling pattern in the digital image.

The transmission device <NUM> may transmit the digital image and information related to the digital image (e.g., the magnification, etc.) to, for example, a mobile device or the like.

In some examples according to the present disclosure, since specifications of the sample plates may be different, the parameters such as the length and/or spacing of the tick marks of the scaling pattern on the sample plates with different specifications may be different. In this case, the processor <NUM> may also need to further combine the pattern information related to the digital image to determine the magnification of the microscopic device.

In addition, in some examples according to the present disclosure, the processor <NUM> may also determine the direction of the sample plate where the sample is located based on the pattern information. For example, when the sample plate is the sample plate <NUM> shown in <FIG>, the pattern information may indicate that the direction of the arrow is the same as the longitudinal direction of the sample plate <NUM>. In this way, the processor <NUM> may recognize the direction of the arrow of the scaling pattern from the digital image, and designate the direction of the arrow as the longitudinal direction of the sample plate.

Further, in some examples according to the present disclosure, the processor <NUM> may classify digital images based on pattern information. For example, the digital images may be classified based on the size of the scaling pattern, and digital images with the same size of the scaling pattern may be divided into a group. When browsing the group of digital images later, the digital images may be scaled to make the size of the scaling pattern the same, so that users may intuitively observe and compare the relative size of the samples in each digital image.

Further, in some examples according to the present disclosure, the processor <NUM> may generate a first image from the pattern information and integrate the first image into the digital image. For example, as shown in <FIG>, for the sample plate shown in <FIG>, the processor <NUM> may obtain that the length L of the tick mark is <NUM> based on the pattern information. The processor <NUM> may generate a message with the word "<NUM>," and the first image may be integrated into the digital image. In the synthesized digital image, the value of the length L of the tick mark may be marked near the tick mark, so that the user may more intuitively understand the size of the sample when browsing the digital image.

In addition, the processor <NUM> may classify the digital images based on the first sample information. For example, when the first sample information includes the type of the samples, the processor <NUM> may determine that the digital images of samples of the same type belong to the same group.

In addition, in some examples according to the present disclosure, the first sample information may also include other information such as production date, photographing date, source, copyright information, or the like. The processor <NUM> may also divide the digital images with the same date into a group.

In some examples according to the present disclosure, the processor <NUM> may generate a second image based on the first sample information and integrate the second image into the digital image. As shown in <FIG>, when the first sample information indicates that the type of the samples is human breast cancer cells (MCF-<NUM> cells), the processor <NUM> may generate a second image <NUM> including the word "MCF-<NUM> cells" and integrate the image <NUM> into the digital image. In this way, when the digital image is displayed on a display, for example, the type of the sample may be directly known.

In some examples according to the present disclosure, a client may find and download the digital image from the server. For example, the client may enter a keyword, such as yeast cells, and the keyword may be transmitted to a remote server. The server may find digital images of yeast cells in all sample information in the database based on the keyword, and provide a list or thumbnails of these digital images to the client. The client may select and download a selected digital image and related information of the selected digital image based on the information provided by the server. Further, in some examples according to the present disclosure, the client may pay a fee to the server to obtain a license to use the selected digital image. After the server determines that the client has obtained the license, the selected digital image may be transmitted to the client.

Further, in some examples according to the present disclosure, the processor <NUM> may analyze the digital image based on the scaling pattern to obtain second sample information related to the sample. The second sample information may include, for example, diameters of the samples, values of major axis and values of minor axis of the samples, a size of the visual field, a concentration of the samples and other information.

For example, <FIG> is another schematic diagram illustrating a microscopic image according to some examples of the present disclosure. As shown in <FIG>, based on the pattern information, the processor <NUM> may determine that the length unit of the scaling pattern in the digital image is <NUM>. Based on a determination that the length unit of the scaling pattern in the digital image is <NUM>, the magnification of the digital image in <FIG> may be determined as <NUM>. Based on the first sample information, the processor <NUM> may further determine that the type of sample in the digital image is yeast cells. Based on the information that the type of sample in the digital image is yeast cells, the processor <NUM> may perform an image recognition operation on identifying yeast cells. For example, the processor <NUM> may determine a yeast cell <NUM> based on the image recognition operation and determine that the diameter of the yeast cell <NUM> is <NUM> based on the scaling pattern, the diameter of the yeast cell <NUM> may be stored in the second sample information.

Further, in some examples according to the present disclosure, the processor <NUM> may determine a plurality of yeast cells by the image recognition operation and determine the diameter of each of the plurality of the yeast cells based on the scaling pattern. Then, the processor <NUM> may store an average value of the diameters of the plurality of yeast cells in the second sample information as a diameter of the plurality of yeast cells.

For example, as shown in <FIG>, the processor <NUM> may identify yeast cells <NUM>, <NUM>, and <NUM> from a digital image. Based on the scaling pattern, the diameter of these yeast cells may be determined as <NUM>, <NUM>, and <NUM>. The average value of the diameters is <NUM>. The processor <NUM> may store the average value in the second sample information as the diameter value of the samples.

In addition, in some examples according to the present disclosure, the processor <NUM> may identify <NUM> yeast cells from the digital image and determine the diameter of each of the <NUM> yeast cells, so that the average value of the diameters of the <NUM> yeast cells may also be obtained and stored in the second sample information.

In addition, the processor <NUM> may also determine the size of a visual field of photographing and the concentration of the samples from the digital image. As shown in <FIG>, the processor <NUM> may determine that the area of the sample plate in the digital image is <NUM>×<NUM><NUM> based on the scaling pattern. In addition, as described above, the type of sample plate may also be determined based on the scaling pattern, so that the depth of the sample cell may be obtained as <NUM>. In this way, the processor <NUM> may determine that the concentration of yeast cells is about <NUM>×<NUM><NUM>/ml.

In addition, the processor <NUM> may determine the value of the major axis and the value of the minor axis of the sample from the digital image. For example, <FIG> is another schematic diagram illustrating a microscopic image of chlorella according to some examples of the present disclosure. The processor <NUM> may determine the value of the major axis and the value of the minor axis of each chlorella based on the scaling pattern in <FIG>, and further determine that the average value of the minor axis of the chlorella is about <NUM>, and the value of the major axis of the chlorella is about <NUM>.

According to the example of the present disclosure, a microscopic analysis system is also provided, including the microscopic device, the image processing device, the mobile device, etc. It should be understood that the image processing device of the present disclosure may be a single server or multiple servers, or a cloud server.

As shown in <FIG>, the mobile device may control the microscopic device by the cloud server (for example, adjusting the photographing parameter, etc.), or receive the microscopic image captured by the microscopic device by the cloud server. The cloud server may transmit an update of an application to the microscopic device and/or the mobile device. In addition, a plurality of microscopic devices <NUM>~N may be connected to the cloud server at the same time. The mobile device may browse the image captured by a specified microscopic device or control the operation of the microscopic device as needed. The cloud server may store and analyze microscopic images captured by the plurality of microscopic devices, and may transmit the microscopic images and an analysis result to the mobile device.

In each of the above examples, the scaling pattern is arranged in the sample plate. In some embodiments according to the present disclosure, the scaling pattern may be arranged in an optical imaging device of the microscopic device. For example, a transparent glass plate with a scaling pattern may be integrate to a lens group of the optical imaging device. In this way, the actual magnification of sample imaging may also be obtained based on a conversion of imaging magnification.

Further, in some examples according to the present disclosure, the sample may be yeast and the yeast may be counted.

<FIG> is a flowchart illustrating a method for counting yeast according to some examples of the present disclosure. As shown in <FIG>, in the method, a microscopic image of yeast may be captured first, and the microscopic image may also include a scaling pattern for determining a magnification (operation <NUM>).

Then, the magnification may be determined based on the scaling pattern in the microscopic image (operation <NUM>).

Next, a count of the yeast in the microscopic image may be determined (operation <NUM>).

Finally, a concentration of the yeast may be determined based on the magnification and the count of the yeast (operation <NUM>).

The method for counting yeast according to the present disclosure may be described in further detail below in combination with embodiments.

The operation of photographing the yeast with a microscopic device is shown as follows.

Dyeing solution may be prepared first. Methylene violet or methylene blue may be used for dyeing. For example, <NUM>% sodium citrate dihydrate methylene violet solution (including <NUM>% methylene violet solution) may be prepared as follows: selecting <NUM> methylene violet and <NUM> trisodium citrate dihydrate, and then adding distilled water to make volume of the solution to <NUM>.

In an embodiment, <NUM>% sodium citrate dihydrate methylene violet solution (including <NUM>% methylene blue solution) may also be prepared as follows: selecting <NUM> methylene blue and <NUM> trisodium citrate dihydrate, and then adding distilled water to make volume of the solution to <NUM>.

Then, a sample of yeast may be taken. For yeast sludge or a sample having a high concentration of yeast, the sample may be diluted to a certain concentration range by using diluent.

Next, <NUM> of the sample of yeast may be mixed with <NUM> of the dyeing solution, and the mixed solution may be placed in a sample cell of the sample plate according to the above examples of the present disclosure.

Finally, the sample plate accommodating the sample may be placed on the sample table of the microscope device <NUM> and a microscopic image may be captured.

For example, <FIG> is another schematic diagram illustrating a microscopic image of the yeast captured by the microscope device according to some examples of the present disclosure.

The processor <NUM> of the microscopic device <NUM> identifies and determines the count of the yeast in the microscopic image based on an image identification algorithm stored in the memory <NUM>. After identification and determination, the count of the yeast in the microscopic image may be determined as <NUM>.

Further, the depth and/or width of the sample cell is determined based on a type of sample plate.

Theprocessor <NUM> of the microscope device <NUM> determines the type of sample plate based on the scaling pattern on the sample plate. A sample plate is the sample plate <NUM> shown in <FIG>. The scaling pattern <NUM> on the sample plate <NUM> includes a second mark <NUM>. The serial number of the sample plate is determined based on the second mark <NUM>. The processor <NUM> may search the database of the memory <NUM> based on the serial number of the sample plate, so as to determine the type of sample plate and the depth and/or width, or length of the sample cell.

After determining the depth of the sample cell, the concentration of the sample of yeast isdetermined. For example, in the microscopic image of the yeast shown in <FIG>, the magnification may be determined as <NUM> based on the scaling pattern. It could be known that the area of the sample cell corresponding to the microscopic image is <NUM>×<NUM><NUM>. In addition, based on the type of the sample plate or the type of the sample cell inputted by the user, the processor <NUM> may search and determine the depth of the sample cell corresponding to the type of the sample plate or the type of the sample cell in the database of the memory <NUM>. Therefore, the concentration of the sample of yeast may be <NUM>×<NUM><NUM>/ml.

In addition, when the scaling pattern includes a third mark for identifying the sample cell, the processor <NUM> may also determine the type of the sample cell based on the third mark, and the size information such as the depth, width and length of the sample cell may be determined based on the type of the sample cell, and then volume of the sample cell may be determined.

In addition, the image processing device may also analyze the microscopic image of the yeast to obtain an analysis result. For example, the analysis results may include at least one of the following parameters: a concentration of alive yeast, a concentration of dead yeast, a total concentration of the yeast, a mortality rate of the yeast, a survival rate of the yeast, an average diameter of the yeast, an average circularity of the yeast, a bud rate of the yeast, or an aggregation rate.

<FIG> is a flowchart illustrating a method for analysis of yeast according to some examples of the present disclosure. As shown in <FIG>, the method for analysis of yeast according to the embodiment of the present disclosure mainly includes the following operations:.

A microscopic image of yeast is received by a cloud server, wherein the microscopic image includes a scaling pattern for determining a magnification (operation <NUM>);.

The magnification is determined by the cloud server based on the scaling pattern (operation <NUM>); and.

The microscopic image is analyzed by the cloud server based on the magnification and an analysis result may be obtained (operation <NUM>).

For example, <FIG> is a schematic diagram illustrating a microscopic image of yeast captured by the microscopic device according to some examples of the present disclosure. Table <NUM> shows an example of the analysis result of the microscopic image of <FIG>.

As shown in Table <NUM>, the type of yeast in the microscopic image of <FIG> is beer yeast. The image processing device counts the live yeast and dead yeast in the microscopic image, so that the count of alive yeast is <NUM> and the count of dead yeast is <NUM>.

In addition, as described above, the image processing device may further obtain the depth of the sample cell (e. , based on the type of sample plate). Then, based on the depth of the sample cell and the area of the sample cell in the microscopic image (which may be determined based on the magnification), the concentration of the yeast, such as the concentration of alive yeast, the concentration of dead yeast and/or the total concentration of yeast concentration may be determined. That is, the image processing device may determine the concentration of alive yeast, the concentration of dead yeast and/or the total concentration of yeast concentration based on the depth of the sample cell, the count of alive yeast, the count of dead yeast and the magnification.

In addition, the image processing device may generate a histogram based on the microscopic images of a plurality of samples and transmit the histogram to the client. For example, <FIG> is a histogram illustrating a concentration of yeast according to some examples of the present disclosure. As shown in <FIG>, the horizontal axis represents different samples and the vertical axis represents concentrations. The concentration of alive yeast and total concentration of yeast of each sample are displayed in <FIG>, thus the users may intuitively understand and compare the concentration of yeast of each sample.

In addition, the image processing device may also generate cell growth curve (CTC curve) based on microscopic images of different samples. As shown in <FIG>, CTC curve is a common way to determine an absolute growth count of cells. The CTC curve may reflect a change of a count of cells with time in the same group of samples.

In addition, the CTC curve may also designate parameters such as a count of yeast (for example, the count of alive yeast, the count of dead yeast, the total count of yeast), the viability rate, the average diameter, the average compactness, the aggregate rate, etc., as the vertical axis, to show a relationship between these parameters and processing time.

In addition, as shown in Table <NUM>, the image processing device may determine diameter of each yeast based on the magnification, and average diameter of yeast may be determined based on the diameter of each yeast and the total count of yeast. In some examples, the image processing device may also generate a histogram of the diameter of yeast, so that the user may more clearly and intuitively understand the distribution of the diameter of yeast.

<FIG> is a histogram illustrating the diameter of yeast according to an example of the present disclosure. As shown in <FIG>, in the histogram of the diameter of yeast, the count of yeast with different diameters is shown, in which a count of yeast with diameter approaching <NUM> is <NUM>, a count of yeast with diameter approaching <NUM> is <NUM>, a count of yeast with diameter approaching <NUM> is <NUM>, and a count of yeast with diameter approaching <NUM> is <NUM>. According to <FIG>, it can be seen that the diameter of most yeast is <NUM>-<NUM>.

In addition, since the microscopic images of a plurality of samples are usually stored on the server (such as the cloud server), the histogram of the diameter of yeast of each sample may be integrated to generate an integrated diagram of the diameter of yeast. <FIG> is an integrated diagram illustrating the diameter of yeast according to an example of the present disclosure. As shown in <FIG>, the histogram of the diameter of yeast of three samples is integrated. The diameter of yeast and distribution of different samples may be intuitively compared.

In addition, the image processing device may also determine the count of aggregated yeast by performing an image processing operation on the microscopic image, and the aggregation rate may be determined based on the total count of yeast and the count of the aggregated yeast. For example, the image processing device may identify a count of yeast aggregates, a count of yeast in each yeast aggregate based on the image processing operation, so the aggregation rate may be determined as follows
the aggregation rate of yeast= (Σ the count of yeast in each yeast aggregate)/ the total count of yeast.

In addition, the image processing device may also generate a histogram of yeast aggregates. <FIG> is a histogram illustrating yeast aggregates according to an example of the present disclosure. As shown in <FIG>, in the histogram of yeast aggregates, the abscissa is the count of yeast in a yeast aggregate, and the ordinate is the count of the yeast aggregates. As shown in <FIG>, for the microscopic image of the sample of yeast shown in <FIG>, the count of yeast aggregates including <NUM> yeast is <NUM>, the count of yeast aggregates including <NUM> yeast is <NUM>, the count of yeast aggregates including <NUM> yeast is <NUM>, the count of yeast aggregates including <NUM> yeast is <NUM>, the count of yeast aggregates including <NUM> yeast is <NUM>, the count of yeast aggregates including <NUM> yeast is <NUM>, the count of yeast aggregates including <NUM> yeast is <NUM>, the count of yeast aggregates including <NUM> yeast is <NUM>, the count of yeast aggregates including <NUM> yeast is <NUM>, the count of yeast aggregates including <NUM> yeast is <NUM>, the count of yeast aggregates including <NUM> yeast is <NUM>, the count of yeast aggregates including <NUM> yeast is <NUM>, and the count of yeast aggregates including <NUM> yeast is <NUM>. As shown in <FIG>, in the case of yeast agglomeration, most yeast aggregates may include <NUM>-<NUM> yeast.

In addition to the histogram described above, the image processing device may also generate other types of diagrams, such as a pie chart, or the like.

In addition, the image processing device may perform an image processing operation on the microscopic image to determine other parameters. For example, the circularity of each yeast may be determined by the image processing operation, and the average circularity of yeast may be determined based on the circularity of each yeast and the total count of yeast.

In some examples according to the present disclosure, the image processing device may also perform an image processing operation on the microscopic image to determine the count of budding yeast, and the bud rate of yeast may be determined based on the total count of yeast and the count of budding yeast. The bud rate is one of the important quality standards reflecting the growth of yeast. For example, in some embodiments, a yeast with a bud volume less than <NUM>/<NUM> of the mother yeast may be used as a budding yeast, and a yeast with a bud volume greater than <NUM>/<NUM> of the mother yeast may be used as two yeast, and then the bud rate of yeast may be determined as follows
the bud rate of yeast= the budding yeast/ the total count of yeast.

In addition, as described above, the server may be, for example, a remote server or a cloud server, and the image processing device may be, for example, an image processing module running on the remote server or the cloud server. In the example of the present disclosure, since the magnification may be accurately determined based on the ruler pattern on the microscopic image, the microscopic images captured by different microscopic devices may be compared, and a integrated diagram of the histogram of the diameter of yeast as described above may be generated.

The terms "front", "back", "top", "bottom", "over", and "under" in the present disclosure and claims, if present, are used for descriptive purposes and are not necessarily used to describe invariant relative positions. It is to be understood that the terms so used are interchangeable under appropriate circumstances, enabling the embodiments of the disclosure described herein. For example, capable of operating in other orientations than those shown or otherwise described herein.

As used herein, the term "exemplary" means "serving as an example, instance, or illustration" rather than as a "model" to be exactly reproduced. Any implementation illustratively described herein is not necessarily to be construed as preferred or advantageous over other implementations.

As used herein, the term "substantially" is meant to encompass any minor variation due to design or manufacturing imperfections, tolerances of devices or elements, environmental influences, and/or other factors. The term "substantially" also allows for differences from a perfect or ideal situation due to parasitic effects, noise, and other practical considerations that may exist in an actual implementation.

The above description may indicate elements or nodes or features that are "connected" or "coupled" together. As used herein, unless expressly stated otherwise, "connected" means that one element/node/feature is electrically, mechanically, logically, or otherwise directly connected to another element/node/feature (or direct communication). Similarly, unless expressly stated otherwise, "coupled" means that one element/node/feature can be mechanically, electrically, logically, or otherwise linked, directly or indirectly, with another element/node/feature to Interactions are allowed, even though the two features may not be directly connected. That is, "coupled" is intended to encompass both direct and indirect coupling of elements or other features, including connections that utilize one or more intervening elements.

In addition, certain terms may also be used in the following description for reference purposes only, and are thus not intended to be limiting. For example, the terms "first," "second," and other such numerical terms referring to structures or elements do not imply a sequence or order unless the context clearly dictates otherwise.

It should also be understood that the word "including/comprising" is used herein to indicate the presence of the indicated features, integers, steps, operations, units, and/or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, units and/or components and/or combinations thereof.

In the present disclosure, the term "providing" is used in a broad sense to encompass all manners of obtaining an object, thus "providing something" includes, but is not limited to, "purchasing," "preparing/manufacturing," "arranging/setting," "installing/ assembling," and/or "ordering" the objects, etc..

Those skilled in the art should appreciate that the boundaries between the operations described above are merely illustrative. Multiple operations may be combined into a single operation, a single operation may be distributed among additional operations, and operations may be performed at least partially overlapping in time. Furthermore, alternative examples may include multiple instances of a particular operation, and the order of operations may be changed in other various examples.

However, other modifications, changes, and substitutions are equally possible. Accordingly, the present disclosure and drawings are to be regarded in an illustrative rather than a restrictive sense.

Claim 1:
A method for analysis of yeast, comprising:
capturing a microscopic image of yeast in a sample cell (<NUM>) on a sample plate (<NUM>) by a microscopic device (<NUM>) and transmitting the microscopic image to a cloud server, wherein the sample plate (<NUM>) includes a plurality of sample cells (<NUM>);
receiving the microscopic image of the yeast in the sample cell (<NUM>) on the sample plate (<NUM>) by the cloud server, wherein the microscopic image includes a scaling pattern (<NUM>) for determining a magnification, and wherein the scaling pattern (<NUM>) is included on the sample plate (<NUM>), the scaling pattern (<NUM>) including a first mark (<NUM>) for identifying the sample plate (<NUM>) and a second mark (<NUM>) for identifying the sample cell (<NUM>);
determining the magnification by the cloud server based on the scaling pattern (<NUM>);
determining, by the cloud server, a first serial number of the sample plate (<NUM>) based on the first mark (<NUM>) or determining a second serial number of the sample cell (<NUM>) based on the second mark (<NUM>);
determining, by the cloud server, a depth of the sample cell (<NUM>) based on the first serial number or the second serial number; and
analyzing, by the cloud server, the microscopic image based on the magnification and the depth of the sample cell (<NUM>) to obtain an analysis result,
wherein the analyzing the microscopic image based on the magnification and the depth of the sample cell (<NUM>) comprises:
performing, by the cloud server, an image processing operation on the microscopic image to determine a count of the yeast in the microscopic image;
obtaining the depth of the sample cell (<NUM>) by the cloud server; and
determining, by the cloud server, a total concentration of the yeast based on the depth of the sample cell (<NUM>), the count of the yeast, and the magnification.