Method for determining the production frequency of a series of moving drops in a fluidic channel

Abstract

The invention relates to a method for determining the production frequency of a series of droplets (2) moving in a fluidic channel (31), the method comprising the following steps: - acquisition, by means of a rolling shutter image capture device (11), of an initial image of at least two droplets in series in the fluidic channel, the initial image comprising a pixel matrix forming rows and columns, the rows being acquired sequentially one after the other by means of the rolling shutter; - detection, from the initial image, of a contour of at least one of the two droplets; - calculation of the production frequency based on the contour, a delay between the acquisition of two successive rows of pixels, and a distance between the two droplets. Figure for the abstract: Fig. 1.

Description

Title of the invention: Method for determining a production frequency of a series of drops moving in a fluid channel Technical field

[0001] The present invention relates generally to the technical field of fluidics.

[0002] It relates more particularly to a method for determining a frequency of production or passage of a series of drops in motion in a fluid channel.

[0003] The invention finds a particularly advantageous application in the realization of a control of the frequency of production of drops on a reference frequency. Technological background

[0004] Obtaining regular production of a series of drops in a fluidic system, in particular in microfluidic systems, i.e. at a predetermined reference or setpoint frequency, is a major challenge, in particular with a view to dynamic sorting of these drops. However, it is not sufficient for the pressure or injection flow rate of the fluids, typically oil and water, to be fixed to obtain regular production of drops in series, in particular microdrops.

[0005] Indeed, the frequency of drop production depends on the pressure within the fluid channel in which the drops are produced, and this pressure within the channel takes a certain time to establish itself. The narrower the channel, the longer it takes. Thus, with a constant pressure and flow rate of fluid injections, the frequency of drop production varies over time.

[0006] It is therefore necessary to measure, on the drops moving within the channel, this production frequency to compare it to the reference frequency in order to be able to establish a counter reaction by adjusting the pressure or the injection flow rate of the fluids.

[0007] There are electrical methods, based on impedance or wave detection of the drops, to measure the frequency of drop production. These methods, however, suffer from a low maximum detectable frequency (less than 3 kHz) since the drops must be sufficiently spaced apart to be detected. These methods are therefore unsuitable for a large number of applications.

[0008] There are also optical methods for measuring higher production frequencies that can reach several tens of kilohertz. Some of These optical methods are based on fluorescent coding, which requires loading the drops with a fluorescent liquid, using a laser and a very sensitive detector (because the fluorescent signal is weak). To do without fluorescence, other methods are based on very high frequency imaging combined with serial drop counting. In both cases, these methods require expensive detectors.

[0009] The need thus arose to measure at low cost the frequency of production of drops in the fluidic channel. Summary of the invention

[0010] In this context, the present invention provides a method for determining a production frequency of a series of drops moving in a fluid channel, the method comprising the following steps: - acquiring, by means of a rolling shutter image capture device, an initial image of at least two drops in series in the fluidic channel, the initial image comprising a matrix of pixels forming rows and columns, the rows being acquired sequentially one after the other by means of the rolling shutter; - detection, from the initial image, of an outline of at least one of the two drops - calculation of the production frequency based on the contour, a delay between the acquisition of two successive lines of pixels, and a distance between the two drops.

[0011] Thus, thanks to the invention, the frequency of production of the drops is determined by means of a rolling shutter image capture device, that is to say an inexpensive image capture device. Rolling shutter image capture devices are in fact very inexpensive, in particular in comparison with global shutter devices used in the very high frequency imaging methods of the prior art.

[0012] Remarkably and counter-intuitively, the contour of a drop provides information on the movement of the drop in the channel thanks to the temporal information contained in the image. Indeed, since this single image is acquired line by line, i.e. sequentially, the shape of the contour of the drop on this image depends on the speed of the drop. Thus, evaluating a deformation of the drops via their contour therefore makes it possible to determine their movement in the channel.

[0013] Therefore, by combining the measurement of the deformation (which makes it possible to deduce the deformation rate) with a simple measurement of the distance between the two drops, the invention makes it possible to determine the production frequency inexpensively. Advantageously, the method of the present disclosure does not require fluorescent coding of the droplet.

[0014] Remarkably, since the initial image is composed of pixels, the deformation rate is expressed in pixels per unit of time and the distance between the two microdrops is expressed in pixels. Thus, the dimension of the ratio of the deformation rate to the distance, i.e. the production frequency, is directly the inverse of a time. It is therefore not necessary to determine a speed of the drop in meters per unit of time, which requires determining a large number of parameters of the optical system, in particular the magnification of the optical imaging system.

[0015] In other words, the method according to the invention does not require any calibration to determine the frequency of production of the drops since the “pixel” dimension is eliminated in the ratio of the deformation rate to the distance. This makes the invention very simple to implement.

[0016] Other advantageous and non-limiting characteristics of the method according to the invention, taken individually or in all technically possible combinations, are the following: - it is planned to: construct derived images from the initial image, each derived image being associated with an offset value, the lines of each derived image being successively translated, relative to their position on the initial image, by a number of pixels proportional to the offset value associated with said derived image; detect, on each derived image, a contour derived from said at least one of the two drops; determine the production frequency on the basis of the derived contours deduced from the derived images; - the offset values ​​are increasing from 1 to a positive integer and each line of each derived image is translated, relative to its position on the initial image, by a number of pixels equal to the offset value multiplied by an index of said line; - it is planned to: calculate a circularity index of each derived contour associated with each derived image; determine an adjustment curve of the circularity indices as a function of the offset values; determine the production frequency as a function of a minimum of the adjustment curve; - it is intended to determine a deformation, which is representative of a difference between a shape of said at least one of the two drops on the initial image and a circular shape, on the basis of a difference in position between a first end of said at least one of the two drops in a line of pixels which is acquired first during the acquisition step and a second end of said at least one of the two drops in another line of pixels which is acquired last during the acquisition step, the production frequency also being calculated on the basis of the deformation; - it is planned to: detect an outline of the other of the two drops, calculate the production frequency on the basis of an average of the outline of said at least one of the two drops and the outline of the other of the two drops; - an initial image acquisition time is less than 10 ms; - the fluid channel having a longitudinal direction, it is planned, before the acquisition step, to arrange the image capture device relative to the fluid channel so that, on the initial image, the longitudinal direction of the fluid channel forms an angle of less than 10 degrees with the lines; - it is planned to illuminate the fluid channel and said at least two drops throughout the acquisition by means of a light source; - it is planned to determine a center of gravity of each of the two drops and to calculate the distance between the two drops as the distance between the two centers of gravity; - it is intended to determine a speed of said at least one of the two drops on the basis of the contour, the delay and taking into account at least one optical parameter of the image capture device or a predetermined distance represented on the initial image.

[0017] The invention also provides a method for producing a series of drops, the series of drops being in motion in a fluidic channel of a fluidic device, the method comprising the following steps: - selection of a reference frequency for the production of the series of drops; - determination of a production frequency of the drop series in the fluid channel by a method as described above; - comparison of the production frequency and the reference frequency; - determination, on the basis of the comparison, of a flow rate or pressure setpoint for a fluid injected into the fluidic device upstream of the fluidic channel to produce the series of drops.

[0018] The invention also relates to a device for determining a production frequency of a series of drops moving in a fluid channel, the system comprising an image capture device with a rolling shutter adapted to acquire an initial image of at least two drops in series in the fluid channel, the initial image comprising a matrix of pixels forming rows and columns, the rows being acquired sequentially one after the other by means of the rolling shutter, and a computer programmed to implement: - the detection, from the initial image, of an outline of at least one of the two drops; - the calculation of the production frequency, based on the contour, of a delay between the acquisition of two successive lines of pixels and a distance between the two drops.

[0019] The invention finally relates to a drop sorting system comprising a device as described above.

[0020] Advantageously, the system is a microfluidic device or a flow cytometer.

[0021] Of course, the various features, variants and embodiments of the invention may be combined with each other in various combinations to the extent that they are not incompatible or mutually exclusive. Description of the invention

[0022] The description which follows with reference to the appended drawings, given as non-limiting examples, will make it clear what the invention consists of and how it can be implemented.

[0023] In the attached drawings:

[0024] [Fig-1] is a schematic view of a system for determining a frequency of production of moving drops in a fluid channel.

[0025] [Fig.2] is a schematic illustration of a rolling shutter image acquisition showing operations on sensor lines as a function of time (t).

[0026] [Fig.3] is a block diagram of a sequence of steps for determining the speed and frequency of production of moving drops in a fluid channel using the system of [Fig.l].

[0027] [Fig.4] is an image acquired sequentially, by means of the system of [Fig.l], of a plurality of drops moving in a fluid channel.

[0028] [Fig.5] is an image derived from the image of [Fig.4] constructed by shifting the pixel lines with a first shift value.

[0029] [Fig.6] is another image derived from the image of [Fig.4] constructed by shifting the pixel lines with another shift value.

[0030] [Fig.7] is yet another image derived from the image of [Fig.4] constructed by shifting the pixel lines with yet another shift value.

[0031] [Fig.8] is a representation of a processing of the image of [Fig.6] illustrating a determination of the contours of the drops.

[0032] [Fig.9] is a graphical representation of droplet circularity indices on derived images (as shown in Figures 6, 7 and 8) as a function of the offsets used to construct the derived images, as well as a fitting curve for determining an optimum offset value.

[0033] [Fig. 10] is a schematic representation of a drop of the plurality of drops of [Fig.4] making it possible to determine a deformation of the drops.

[0034] [Fig. 11] is a block diagram of a sequence of steps allowing the production of drops with regulation of their production frequency.

[0035] [Fig.l] represents a system 1 for determining a production frequency fp of a series of drops 2 moving in a fluidic device 3. The drops 2 are more particularly moving in a fluidic channel 31 of the fluidic device 3. As shown in [Fig.l], the fluidic channel 31, hereinafter called channel 31, is here rectilinear in a longitudinal direction. The drops 2 thus have a rectilinear translational movement in the channel 31. In [Fig.4], the drops 2 move rectilinearly from left to right parallel to the longitudinal direction of the channel 31. As shown in [Fig.l], the drops 2 of the series are located one behind the other along the longitudinal direction, this means that the series of drops 2 forms a line of drops 2.

[0036] In the embodiment described here, that is to say with reference to Figures 1 to 11, the fluidic device 3 is more particularly a microfluidic device 3, also called a microfluidic chip, as shown in [Fig.l]. In this example, the channel 31 is then a microfluidic channel. The section of the channel 31 is then for example between 10 pm2 and 150,000 pm2 and the length between 50 pm and 1 cm. The drops 2 are then more particularly microdrops 2, which means that their size, i.e. here their diameter, is for example between 1 pm and 300 pm.

[0037] The drops 2 have in the channel 31 a shape which is generally spherical or a flattened sphere shape. The fluidic device 3 is here substantially flat. The plane of the fluidic device 3, referenced PI in [Fig.l], is in particular parallel to the main direction. Parallel to this plane PI, the drops 2 have a circular shape, which means that their outline is generally a circle.

[0038] The microfluidic device 3 also comprises a central injection channel 32 and two lateral injection channels 33 opening onto a junction 35 with the central channel 32, on either side of, and perpendicular to, this junction 35. The central channel 32 contains a sample liquid which is for example pure water or an aqueous medium such as phosphate buffered saline (PBS), and the lateral channels 33 a sheath liquid which is for example oil. In this case, the drops 2 are then microdrops of water suspended in the oil. The drops 2 are produced when the oil flows 4 divide the water flow 5 into separate volumes. The production of the drops 2 takes place here at the junction 35 of the central channel 32 with the lateral channels 33. After having passed through the channel 31, the drops 2 are for example collected in a reservoir 34 connected to the outlet of the channel 31.

[0039] Preferably, the drops 2 are sorted (mechanism not shown) before being collected. For this, the drops 2 are for example analyzed by fluorescence using a laser. When a drop of interest is detected, it is then extracted channel to be oriented in a collection channel. Knowing the production frequency fp of the drops 2 is then important to synchronize the extraction of the drop from the liquid flow.

[0040] Other configurations of the microfluidic device 3 are conceivable. Similarly, other sample liquids and other sheath liquids can be used, for example to form microdrops of oil suspended in water.

[0041] As a variant of the example shown in the figures, the fluidic device is a flow cytometer. The drops then have a diameter which is for example between 30 μm and 300 μm. The fluidic channel can then be open in the sense that it is not delimited by glass or plastic walls but by air. The drops are produced in the flow by the vibration of a piezoelectric actuator.

[0042] Generally, the production frequency fp of the drops 2 is here defined as the inverse of the time separating the production of two successive drops 2, i.e. two drops 2 produced one after the other. The production frequency fp is here equal to the frequency of passage in the microfluidic channel 31.

[0043] As shown in [Fig.l], the system 1 comprises an image capture device 11 arranged to acquire at least one image of the drops 2. The channel 31 comprising the drops 2 is located in the field of view C of the image capture device 11. Here, the system 1 also comprises a light source 12 located opposite the image capture device 11 with respect to the channel 31. The channel 31 is thus interposed between the light source 12 and the image capture device 11 so as to be imaged by transparency. Alternatively, the illumination can be done on the same side as the image capture device, by reflection on the fluidic device 3.

[0044] To simplify understanding, [Fig.l] schematically represents two planes which are in practice distinct and more particularly orthogonal. A first plane is the plane PI of the fluidic device 3 (corresponding to the plane of the figure) and a second plane is that according to which the image capture device 11 and the light source 12 are aligned. In other words, the image capture device 11 and the light source 12 are in practice aligned in a direction perpendicular to the plane of [Fig.l] and the fluidic device 3 represented in [Fig.l] corresponds to an image which could be acquired by the image capture device 11.

[0045] The image capture device 11 more particularly comprises a rolling shutter. Each image that it acquires is thus acquired sequentially in the sense that it is acquired line by line.

[0046] Conventionally, the rolling shutter is here produced electronically.

[0047] The image capture device 11 more particularly comprises a detector consisting of a plurality of sensors, here CMOS sensors, arranged according to a matrix forming rows L1, L2 and columns (the terms rows and columns being interchangeable since they are conventional). The operation of the image capture device 11 is illustrated in [Fig.2]. Each image is acquired sequentially, row of sensors by row of sensors. The first row L1 of sensors, here the top one, is initialized (block I in [Fig.2]), then integrates the light coming from channel 31 illuminated by the light source 12 (block E in [Fig.2]), then the electrical signals produced by the sensors are read (block L in [Fig.2]), i.e. collected by a dedicated electrical circuit.The second line L2 of sensors is acquired with a time shift relative to the first line LL This means that: i) the second line L2 is initialized after the initialization of the first line Ll has finished, ii) the integration times of the two lines partially overlap, iii) the second line L2 is read after the reading of the first line LL has finished As shown in [Fig.2], the same applies to the following lines.

[0048] Thus, the rolling shutter mechanism is obtained by electronic unrolling of the detector.

[0049] Each acquired image comprises a matrix of pixels forming rows and columns. In [Fig. 4], the rows of pixels extend from right to left and the columns from top to bottom. The rows of pixels correspond to the rows L1, L2 of sensors and the columns of pixels correspond to the columns of sensors. In other words, each image is also acquired sequentially row of pixels by row of pixels. Thus, an object moving in the field of view C of the image capture device 11 during image acquisition appears distorted since its different portions are acquired by different rows L1, L2 of sensors at successive times.

[0050] The image capture device 11 also includes its own processor designed to interpret the signals collected by the dedicated electrical circuit in order to construct the images.

[0051] The time between the acquisition of two successive sensor lines, hereinafter called line time tL, is an intrinsic datum of the image capture device 11. The line time tL is more specifically equal to a delay between two identical actions of the image capture device 11 on two successive sensor lines, for example the first line L1 and the second line L2. The line time tL therefore corresponds to the aforementioned time offset. The line time tL is therefore also equal to the delay between the acquisition of a line of pixels and the acquisition of the following line of pixels, that is to say the delay between the acquisition of two successive lines of pixels, the acquisition of a line of pixels starting at the initialization (block I) of the corresponding line of sensors.

[0052] The line time tL is for example the delay between the start of the initialization of a line of sensors and the start of initialization of the next line of sensors (as shown in [Fig.2]) or the delay between the start of reading a line and the start of reading the next line of sensors. In practice, this data is provided by the manufacturer of the image capture device 11. Preferably, the image capture device 11 is selected so as to have a line time tL of less than 10 ps. The line time tL corresponds to a construction parameter of the rolling shutter image capture device 11. The line time tL remains constant for a given rolling shutter image capture device.

[0053] As shown in [Fig.l], the system 1 also comprises a computer 13 configured to control the image capture device 11. The computer 13 here comprises at least one memory and at least one processor. The memory is a computer-readable recording medium comprising instructions which, when executed by the processor, make it possible to control the image capture device 11. The computer 13 is in particular configured to trigger the image captures.

[0054] The computer 13 is more particularly programmed to implement a method for determining the production frequency fp of the drops 2, and this from the capture of a single image 40, subsequently called the initial image 40, by the image capture device 11. This method is here implemented by the system 1. Of course, it can be implemented by any appropriate system which is based on a sequential acquisition of images.

[0055] The method for determining the production frequency fp comprises the following main steps: - acquisition, by means of the image capture device 11 with rolling shutter, of the initial image 40 of at least two drops 2 in the channel 31; - detection, from the initial image 40, of an outline 21 of one of the two drops 2; - determination, on the basis of contour 21, of a deformation rate T of drop 2; - determination of a distance between the two drops 2; - calculation, on the basis of the deformation rate T, the line time tL, and the distance between the two drops 2, of the production frequency fp.

[0056] The method here comprises a step of determining the deformation rate T which is an intermediate parameter used to determine the production frequency fp. The deformation rate T is representative of the movement, i.e. the speed, of the drop 2 in the channel 31. The deformation rate T corresponds here to a partially dimensionless value of the speed of the drops 2 in the sense that it is expressed in pixels per unit of time. The deformation rate T depends on the speed of the drops 2 and the arrangement of the image capture device 3 relative to the channel 31.

[0057] The contour 21 of the drop 2 provides information on the movement of the drop 2 during the acquisition of the initial image 40. Indeed, since the drop 2 advances during the acquisition, its contour 21 appears deformed relative to a circle.

[0058] Preferably, the method comprises a prior step (not shown) of arranging the image capture device 11 relative to the channel 31 so that, on the initial image 40, a main direction DI in which the drops 2 are moving or the longitudinal direction of the microfluidic channel 31 forms an angle of less than 10 degrees with the lines of pixels. Here, the longitudinal direction of the microfluidic channel 31 is parallel to the main direction D1.

[0059] Even more preferably, the initial image 40, the main direction D1 or the longitudinal direction of the microfluidic channel 31 is parallel to the lines of pixels, as is the case in [Fig.4] on which two lines of pixels LP1, LP2 are represented.

[0060] As shown in [Fig. 3], the method begins more particularly with a first step E1 of acquiring the initial image 40. During the first step E1, the light source 12 is here switched on. Preferably, the light source 12 is switched on continuously throughout the entire method.

[0061] In the example shown in [Fig.4], a plurality of drops 2, here about twenty drops 2, is included in the field of view C during the acquisition of the initial image 40. Consequently, the plurality of drops 2 is represented on the initial image 40. As will appear later, having several drops 2 on the initial image 40 makes it possible to determine average (or median) values, which increases the precision of the determination of the production frequency fp. The drops 2 of this plurality, i.e. the drops 2 represented on the initial image 40, are subsequently called “the drops”.

[0062] However, the production frequency fp can be determined on the basis of only two drops 2. In other words, imaging only two drops 2 (therefore successive) can be sufficient to determine the distance and therefore the production frequency fp. On the other hand, imaging a single drop 2 is sufficient to determine the deformation rate T.

[0063] The portion of the channel 31 imaged here is regular, in the sense that it has a constant section over the entire initial image 40. Consequently, the drops 2 all move with the same speed, their deformation rate T is therefore identical. Alternatively, when the portion of the channel 31 imaged is irregular, only a regular section, or the most regular possible, of this portion is taken into account in the method.

[0064] As explained previously, the initial image 40 is acquired pixel line by pixel line. Here, the first line LP1 located at the top of [Fig.4] is acquired first, the other lines are successively acquired starting from the first line LP1.

[0065] Advantageously, when the main direction DI is parallel to the lines of pixels, corresponding portions of the drops 2 are acquired at the same time since they are located on the same line of pixels. The deformations of the different drops 2 represented on the initial image 40 are thus substantially identical, which increases the precision of the determination of the deformation rate T.

[0066] In a first embodiment of the method for determining the deformation rate T, represented in [Fig. 3], the determination of the deformation rate T is based on the construction of derived images 41. The idea of ​​this first embodiment is to recalibrate the initial image 40 by means of the derived images 41 so as to obtain drops 2 of circular shape on at least one derived image 4L. The recalibration making it possible to obtain a circular shape provides information on the displacement of the drops 2 during the acquisition of the initial image 40, and therefore on the deformation rate T of the drops 2.

[0067] Thus, in the first embodiment, the method continues with a second step E2 during which the computer 13 constructs the derived images 4L

[0068] The second step E2 firstly comprises the determination of offset values. Generally, the offset values ​​are positive integers distinct from one another. The offset values ​​are preferably all positive integers from 1 to a maximum offset value N. The offset values ​​can also vary from n to N in steps of p, with n>1 and p>1, for example n=p=5. This makes it possible, at the expense of the precision in determining the deformation rate T, to reduce the calculation time. The maximum offset value N is here predetermined. It is for example between 20 and 1000. The maximum offset value N can here depend on an estimated speed of the drops.

[0069] Each derived image 41 is associated bijectively with an offset value. Each derived image 41 is then constructed by successively translating the pixel lines by a number of pixels proportional to the offset value which is associated with said derived image 4L. Translating here means moving or shifting the pixel lines relative to their position on the initial image 40. In other words, the translation is a shift in the direction of the pixel lines (i.e. from right to left in [Fig.4]). The pixel lines are translated opposite to the movement of the drops 2, i.e. a direction contrary to the movement of the drops 2. This makes it possible to compensate, on the derived images 41, for the deformation of the drops due to their movement during the acquisition of the image 4L. Here, with reference to [Fig.4], the pixel lines are thus translated to the left since the drops are moving to the right.

[0070] Each line of pixels of each derived image 41 is more specifically translated by a number of pixels equal to the offset value multiplied by an index of said line of pixels. By convention, on the initial image 40 illustrated in [Fig.4], the indices are here positive integers counted from the top line, index 1, to the bottom line. This construction of derived images 41 is illustrated in detail in figures 5, 6 and 7.

[0071] [Fig. 5] illustrates a first derived image 41A corresponding to the offset value 5, from the initial image 40 represented in [Fig. 4]. The first line LP1, i.e. the top line with index 1, is translated by 5 pixels (5x1) to the left. Then, the second line LP2, i.e. the line in second position from the top and with index 2, is translated by 10 pixels (5x2) to the left. The first line LP1 and the second line LP2, which are strictly opposite each other on the initial image 40, are therefore now offset by 5 pixels relative to each other on the first derived image 41A. Iteratively, the third line with index 3 is translated by 15 pixels and so on.

[0072] [Fig.6] illustrates a second derived image 41B corresponding to the offset value 10, from the initial image 40 represented in [Fig.4]. The first line of index 1 is translated by 10 pixels (10x1), the second line of index 2 by 20 pixels (10x2) and so on. [Fig.7] illustrates a third derived image 41C corresponding to the offset value 15, from the initial image 40 represented in [Fig.4]. The first line of index 1 is translated by 15 pixels (15x1), the second line of index 2 by 30 pixels (15x2) and so on. In Figures 5 to 7, the shape of droplets 2 appears to be closest to a circular shape for the offset value 10. Beyond the value 10, the circularity of droplets 2 degrades again.

[0073] As an example, 25 derived images 41 are constructed in the second step E2 for offset values ​​ranging from 1 to 25 in steps of 1.

[0074] Once the derived images 41 have been constructed, the method continues with a third step E3 of detecting the contours 21' of the drops 2 on the derived images 4L. The contours of the drops 2 on the derived images 41 are subsequently called derived contours 21'.

[0075] During the third step E3, the computer 13 detects more particularly the derived contour 21' of each drop 2 on each derived image 4L. Here, only the drops 2 represented in their entirety are taken into account, those partially represented which are located at the edge of the image are excluded.

[0076] The derived contours 21' are for example detected by means of thresholding on the intensity of the pixels. Indeed, as shown in Figures 4 to 7, there is a contrast between the sample liquid and the sheath liquid, which makes it possible to extract the surfaces 22 corresponding to the drops 2. The drops 2 are here darker than the sheath liquid. However, the drops 2 can also appear lighter than the sheath liquid or sometimes as a simple white or black border corresponding to the contour (only the contours are then visible). The method of extracting the derived contours 21' is adapted to the situation.

[0077] The surfaces 22 of the drops represented in [Fig.6] are for example illustrated in [Fig.8]. As shown in [Fig.8], the derived contours 21' are then determined as the edge of these surfaces 22. Preferably, the intensity thresholding is local.

[0078] The derived contours 21' can also be detected by means of a filter for contour detection, such as a Sobel filter or a Kany filter, or by means of a filter for searching for circular objects, for example by a Hough transform.

[0079] The method then comprises a fourth step E4 in which the calculator 13 calculates a circularity index of each derived contour 21'. A circularity index is a value, here positive real, representative of the proximity of shape of a contour 21 or of a derived contour 21' with a circle. A circularity index of a contour 21 or of a derived contour 21' of a drop 2 is for example calculated on the basis of a ratio between the perimeter of the drop 2 and the area of ​​the drop 2. Here, the circularity index is calculated according to the Heywood index. It can also be calculated on the basis of a ratio between a major axis and a minor axis of the drop 2.

[0080] Here, for each derived image 41, an average circularity index is calculated as the average of the circularity indices of each drop 2 represented on the derived image 4L. Following the previous example, the fourth step E4 comprises the calculation of 25 average circularity indices for the 25 derived images 41 constructed in the second step E2.

[0081] The method then comprises a fifth step E5 of determining, on the basis of the average circularity indices, an optimum offset value M. The optimum offset value M is that which best corrects the contour 21 of the drop 2 to approach a circle. The optimum offset value M is here a dimensionless real value. The optimum offset value M is in fact expressed in pixels in the sense that its value is a real number representative of a number of pixels.

[0082] The fifth step E5 here comprises the determination by the computer 13 of an adjustment curve 50 of the average circularity indices as a function of the offset values. Each derived image 41 being associated with an offset value, each average circularity index is therefore also associated with an offset value. A graphical representation of the average circularity indices as a function of the offset values ​​appears in [Fig.9].

[0083] The adjustment curve 50 is here obtained by adjusting, for example by the least squares method, a polynomial function with the offset values ​​as input and the average circularity indices as output. The adjustment curve 50 is thus a polynomial function which statistically represents the average circularity indices as a function of the offset values. The adjustment curve 50 is thus here obtained by a polynomial regression. The polynomial function has, for example, a degree between 2 and 6. Alternatively, the fitting curve could also be obtained by an exponential regression.

[0084] Following the previous example, [Fig.9] illustrates the adjustment curve 50 obtained for the 25 average circularity indices calculated in the fourth step E4.

[0085] Once the adjustment curve 50 has been calculated, the calculator 13 determines the minimum of the adjustment curve 50. This determination is for example carried out by means of an analysis of the derivative of the adjustment curve 50.

[0086] As shown in [Fig.9], in this first embodiment, the optimum offset value M is then defined as the abscissa M of the minimum of the adjustment curve 50. The optimum offset value M is therefore that whose image by the adjustment curve 50 is minimum.

[0087] Thus, remarkably, the precision on the optimum offset value M is greater than the resolution of the initial image 40 (in the sense that it is a value with decimals and not an integer) because all the offset values ​​used to construct the derived images 41 are taken into account with the adjustment curve 50.

[0088] Alternatively, it is possible not to implement the fifth step E5 and simply determine the optimum offset value as equal to the offset value corresponding to the smallest average circularity index.

[0089] The method then comprises a sixth step E6 of calculating the deformation rate T of the drops 2. The deformation rate T of the drops 2 is determined on the basis of the optimum offset value M and the line time tL. The calculator 13 more specifically calculates the deformation rate T as the ratio of the optimum offset value M to the line time tL. The deformation rate dimension T is therefore here the inverse of a time. The line time tL being here expressed in ps, the deformation rate T is expressed in pixels per microsecond.

[0090] As a variant of this first embodiment, the maximum offset value N is not predetermined but the derived images are constructed until a stopping criterion is reached, i.e. without knowing in advance the number of derived images that will be constructed. In other words, a “while” type loop is implemented instead of a “for” type loop. For each derived image, steps E3, E4 and E5 are then implemented so as to calculate the average circularity index of said derived image. This stopping criterion is for example the fact that the last average circularity index calculated (i.e. that of the last derived image constructed) is greater than the average circularity index of the first derived image or the fact that the difference between the last and the penultimate average circularity index is three times greater than the variance of the average circularity indices already calculated. The curve The adjustment curve can also be adjusted as the average circularity indices are calculated. The stopping criterion can then also be the fact that the adjustment curve becomes decreasing again or reaches a second local minimum, the optimum shift value then being defined as the abscissa of the first local minimum of the adjustment curve. The maximum shift value N is then that corresponding to the stopping criterion.

[0091] In a second embodiment, represented in [Fig. 10], the computer determines a deformation of the contour 21 of the drop 2 directly from the initial image 40. The deformation is representative of a difference between a shape of a drop 2 in the channel 31 and a shape of this drop 2 on the initial image 40.

[0092] For a given drop 2, the deformation is then calculated on the basis of a difference in position between: - a first end 24 of the drop 2 which is acquired first; and - a second end 25 of drop 2 which is acquired last.

[0093] This second embodiment can also comprise the detection of the contours 21 of the drops 2 represented on the initial image 40. An average contour can then be reconstructed as the average of these contours 21. The first end 24 and the second end 25 are then respectively the highest point and the lowest point, perpendicular to the direction of the lines of pixels, of the average contour.

[0094] As shown in [Fig. 10], in this second embodiment, the deformation is then equal to the distance D in pixels along the lines of pixels between the first end 24 and the second end 25 of the drop 2 divided by the height H of the drop 2 in pixels along the columns. The drop 2 being of generally circular shape in the plane PI of the fluidic device 3, the first end 24 and the second end 25 should be located vertically to each other on an undistorted image. The deformation is therefore well representative of the displacement of the drop 2 during the acquisition of the image.

[0095] Thus, in this second embodiment, the deformation is representative of the comparison between the shape of this drop 2 on the initial image 40 (directly or via the derived images) with a circle, i.e. with the shape of this drop 2 in the fluidic device 3 parallel to the plane PI of the fluidic device 3.

[0096] Finally, the calculator 13 calculates the deformation rate T as the ratio of the deformation to the line time tL.

[0097] As shown in [Fig.3], whatever the embodiment, the method for determining the production frequency fp then comprises a seventh step E7 of determining a distance between two successive drops 2.

[0098] Preferably, the distance between the two successive drops 2 is an average taken over all the drops 2 represented in the initial image 40. This increases the accuracy of the distance determination, and therefore of the determination of the production frequency fp. For this, the seventh step E7 includes, for example, the calculation of the distance between five drops 2 produced successively, and the division of this distance by four (i.e. the number of intervals between the five drops) to obtain the distance between two successive drops 2.

[0099] The distance between the two successive drops 2 is more particularly a pitch P between these two drops 2. The pitch P is here determined on the basis of the initial image 40. Alternatively, it can be determined on the basis of the derived images 4L

[0100] The pitch P is here a distance between two corresponding points of each drop 2, i.e. the same respective points on each of the drops 2. For example, when the most upstream point (relative to the direction of movement of the drops, i.e. here the leftmost point) of a first drop 2 is considered, the pitch P with the second drop 2 is calculated as the distance between said point and the most upstream point of the second drop 2.

[0101] Preferably, the corresponding points are the centers of gravity G of the drops 2, which makes it possible to average the positions of the drops 2 for a more precise determination of the pitch P. Using the centers of gravity G also makes it possible to overcome possible fluctuations in diameters from one drop to another. Thus, preferably, the pitch P between two drops 2 is the distance between their center of gravity G, as shown in [Fig.4]. The pitch P between the drops 2 is then calculated as the norm of a vector connecting the centers of gravity G of the two drops 2.

[0102] As shown in [Fig. 10]. The centers of gravity G of the drops 2 are here determined by detecting the contours 21 of the drops 2 on the initial image 40 and by determining the barycenters of the contours 21. When the derived images 41 are used, the centers of gravity G of the drops 2 are here determined by detecting the derived contours 21' and by determining the barycenters of the derived contours 21'.

[0103] The method finally comprises an eighth step E8, in which the calculator 13 calculates the production frequency fp by dividing the deformation rate T of the two drops 2 by the distance between the two drops 2.

[0104] Advantageously, the distance between two drops 2 is expressed in pixels in the sense that its value is a real number representative of a number of pixels. Thus, since the deformation rate T is also expressed in pixels (per unit of time), the dimension of the calculated production frequency fp is directly the inverse of a time. In other words, it is not necessary to express the intermediate calculation values ​​(distance, deformation rate) in meters or micrometers to determine the production frequency fp because the “pixel” dimension is cancelled during the division. This avoids the need for calibration of the system or a complex determination of the optical parameters of the system 1. The system 1 can thus be quickly and simply implemented.

[0105] Remarkably, the method makes it possible to determine very high production frequencies fp, for example between 10 and 60 kHz (i.e. 10,000 and 60,000 drops per second). Indeed, as shown in [Fig.4], the method is suitable for determining the production frequency fp of drops 2 very close to each other, or even in contact with each other.

[0106] The method for determining the production frequency fp is here implemented in a method for producing the drops 2 illustrated in [Fig. 11]. The idea of ​​this method is, by determining the production frequency fp throughout the production of the drops 2, to control the production frequency fp to a reference frequency fr.

[0107] The method for producing the drops 2 conventionally comprises producing the drops 2 in the channel 31 by injecting the sample liquid and the sheath liquid by means of pumps and / or syringe pumps.

[0108] As shown in [Fig.l 1], the method for producing the drops 2 begins more particularly with a step E0 of selecting the reference frequency fr for the production of the drops 2. This reference frequency fr makes it possible to estimate initial pressure setpoints, when pumps are used to produce the drops 2, or flow rate, when syringe pumps are used to produce the drops 2. These initial setpoints make it possible to produce the drops 2 whose production frequency fp is determined as described above.

[0109] As explained in the introduction, it is very complex or even impossible to precisely estimate these initial setpoints so as to reach the reference frequency fr since the pressure in the fluidic device 3 varies over time. However, thanks to the measurement of the production frequency fp, the initial setpoints can be modified to stabilize the production frequency fp around the reference frequency fr.

[0110] For this, the method firstly comprises a step E9 of determining the production frequency of the drops 2 in the channel 31 by means of the method of determining the production frequency fp. Here, step E9 corresponds to the combination of steps E1 to E8 described previously.

[0111] The method then comprises a step E10 of comparing the production frequency fp measured in step E9 with the reference frequency fr selected in step E0. During step E10, the calculator 13 here calculates the difference between the production frequency fp and the reference frequency fr.

[0112] The method finally comprises a step El 1 of determining adjusted flow rate or pressure setpoints for the liquids injected into the fluidic device 3 upstream of the channel 31. The adjusted setpoints here comprise one or more flow rate setpoints and / or one or more pressure setpoints. As explained in the introduction, the production frequency varies over time. Thus, the adjusted setpoints are calculated so as to control the production frequency fp to the reference frequency fr. For example, when the production frequency fp is lower than the reference frequency fr, the adjusted setpoint for the liquid injection flow rate of droplets 2 is higher than the reference setpoint, so as to accelerate the production of droplets 2. Conversely, when the production frequency fp is higher than the reference frequency fr, the adjusted setpoint for the liquid injection flow rate of droplets 2 is lower than the reference setpoint, so as to slow down the production of droplets 2.

[0113] As shown in [Fig.2], steps E9, E10 and E11 are implemented iteratively here. Thus, the adjusted setpoints make it possible to correct in real time the temporal variations of the production frequency fp so that it is equal to the reference frequency fr. The adjusted setpoints are therefore scalable over time to maintain the production frequency fp at the initial setpoint value, i.e. at the production frequency fp.

[0114] Advantageously, the method for determining the production frequency fp requires little computing power, in particular because the processing of the initial image 40 is based on simple matrix operations. Thus, it is possible to repeat the determination of the production frequency fp at a high rate, which makes it possible to establish precise and rapid feedback thanks to the adjusted instructions. The step E9 of determining the production frequency fp is for example executed at a rate of between 0.01 and 150 Hz.

[0115] Remarkably, the system 1 also makes it possible to implement a method for determining the speed of the drops 2. The speed of a drop 2 is here expressed in meters (or in units derived from the meter such as micrometers) per unit of time, and not in pixels per unit of time like the deformation rate T. The speed thus corresponds to a dimensioned value of the deformation rate T. Unlike the deformation rate T which depends on the arrangement of the image capture device 11 relative to the fluidic device 3, the speed is an absolute value and independent of this arrangement.

[0116] The speed is thus expressed in dimensioned units of the SL system. For this, it is for example possible to determine the effective size, for example in micrometers, of a pixel of the initial image 40. This can be done by taking into account optical parameters of the image capture device 11, in particular the magnification or the focal lengths of the lenses of the image capture device 11. This can also be done by taking into account a predetermined distance which is represented on the initial image such as the width of the channel which is for example 50 μm.

[0117] The present invention is in no way limited to the embodiments described and re presented, but those skilled in the art will be able to make any variation in accordance with the invention.

[0118] Similarly, the deformation may not be a single real value. For example, the deformation may be a two-dimensional representation of the outline of a drop. The deformation is for example recorded in the form of an array of values. It is then possible to determine the speed by comparing this outline to a list of pre-established outlines, for example during a series of tests with drops traveling through the channel at known speeds. The speed can then be determined by searching for the pre-established outline whose shape is closest to the outline on the initial image, the speed is then determined as the speed corresponding to this pre-established outline.

[0119] The main direction in which a drop is moving can also form an angle greater than 10 degrees with the pixel lines. In an extreme case, the pixel lines (acquired sequentially) can even be perpendicular to the movement. The drop then has an elongated shape with axial symmetry along the main direction. This shape also provides information on the speed, in the sense that it can be determined: the more elongated the drop, the faster it goes.

Claims

Claims

1. Method for determining a production frequency (fp) of a series of drops (2) moving in a fluid channel (31), the method comprising the following steps: - acquiring, by means of an image capture device (11) with a rolling shutter, an initial image (40) of at least two drops (2) in series in the fluid channel (31), the initial image (40) comprising a matrix of pixels forming rows (LP1, LP2) and columns, the rows (LP1, LP2) being acquired sequentially one after the other by means of the rolling shutter; - detecting, from the initial image (40), an outline (21, 21') of at least one of the two drops (2); - calculation of the production frequency (fp) on the basis of the contour (21, 21'), a delay (tL) between the acquisition of two successive lines of pixels (LP1, LP2), and a distance between the two drops (2).

2. Method according to claim 1, in which it is provided to: - construct derived images (41, 41A, 41B, 41C) from the initial image (40), each derived image (41, 41A, 41B, 41C) being associated with an offset value, the lines (LP1, LP2) of each derived image (41, 41A, 41B, 41C) being successively translated, relative to their position on the initial image (40), by a number of pixels proportional to the offset value associated with said derived image (41, 41A, 41B, 41C) - detect, on each derived image (41, 41A, 41B, 41C), a derived contour (21') of said at least one of the two drops (2); - determine the production frequency (fp) on the basis of the derived contours (21') deduced from the derived images (41, 41A, 41B, 41C).

3. Method according to claim 2, in which the offset values ​​are increasing from 1 to a positive integer (N) and in which each line (LP1, LP2) of each derived image (41, 41 A, 41 B, 41C) is translated, relative to its position on the initial image (40), by a number of pixels equal to the offset value multiplied by an index of said line (LP1, LP2).

4. Method according to claim 2 or 3, in which it is provided to: - calculate a circularity index of each derived contour (21') associated with each derived image (41, 41 A, 41 B, 41 C); - determine an adjustment curve (50) of the circularity indices in function of the offset values; - determine the production frequency (fp) as a function of a minimum (M) of the adjustment curve (50).

5. Method according to claim 1, wherein it is provided to determine a deformation, which is representative of a difference between a shape of said at least one of the two drops (2) on the initial image (40) and a circular shape, on the basis of a difference in position between a first end (24) of said at least one of the two drops (2) in a line of pixels which is acquired first during the acquisition step and a second end (25) of said at least one of the two drops (2) in another line of pixels which is acquired last during the acquisition step, the production frequency (fp) also being calculated on the basis of the deformation.

6. Method according to one of claims 1 to 5, in which it is provided to - detect a contour (21) of the other of the two drops (2), - calculate the production frequency (fp) on the basis of an average of the contour (21, 21') of said at least one of the two drops (2) and of the contour (21) of the other of the two drops (2).

7. Method according to one of claims 1 to 6, in which an acquisition time of the initial image (40) is less than 10 ms.

8. Method according to one of claims 1 to 7, the fluidic channel (31) having a longitudinal direction, in which it is provided, before the acquisition step, to arrange the image capture device (11) relative to the fluidic channel (31) so that, on the initial image (40), the longitudinal direction of the fluidic channel (31) forms an angle of less than 10 degrees with the lines (LP1, LP2).

9. Method according to one of claims 1 to 8, in which it is provided to illuminate the fluidic channel (31) and said at least two drops (2) throughout the acquisition by means of a light source (12).

10. Method according to one of claims 1 to 9, in which it is provided to determine a center of gravity (G) of each of the two drops (2) and to calculate the distance between the two drops (2) as the distance between the two centers of gravity (G).

11. Method according to one of claims 1 to 10, in which it is provided to determine a speed of said at least one of the two drops (2) on the basis of the contour (21), the delay (tL) and taking into account at least one optical parameter of the image capture device (11) or a predetermined distance represented on the initial image (40).

12. A method for producing a series of drops (2), the series of drops (2) being in motion in a fluidic channel (31) of a fluidic device (3), the method comprising the following steps: - selecting a reference frequency (fr) for producing the series of drops (2); - determining a production frequency (fp) of the series of drops (2) in the fluidic channel (31) by a method according to one of claims 1 to 11; - comparing the production frequency (fp) and the reference frequency (fr); - determining, on the basis of the comparison, a flow rate or pressure setpoint of a fluid injected into the fluidic device (3) upstream of the fluidic channel (31) to produce the series of drops (2).

13. Device for determining a production frequency (fp) of a series of drops (2) moving in a fluid channel (31), the system comprising an image capture device (11) with a rolling shutter adapted to acquire an initial image (40) of at least two drops (2) in series in the fluid channel (31), the initial image (40) comprising a matrix of pixels forming lines (LP1, LP2) and columns, the lines (LP1, LP2) being acquired sequentially one after the other by means of the rolling shutter, and a computer (13) programmed to implement: - the detection, from the initial image (40), of an outline (21, 21') of at least one of the two drops (2); - the calculation of the production frequency (fp), on the basis of the contour (21, 21'), of a delay (tL) between the acquisition of two successive lines of pixels (LP1, LP2) and of a distance between the two drops (2).

14. A drop sorting system comprising a device according to claim 13.

15. The droplet sorting system of claim 14, wherein the system is a microfluidic device or a flow cytometer.

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