WO2013166022A2 - Machine vision system for frozen aliquotter for biological samples - Google Patents
Machine vision system for frozen aliquotter for biological samples Download PDFInfo
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- WO2013166022A2 WO2013166022A2 PCT/US2013/038880 US2013038880W WO2013166022A2 WO 2013166022 A2 WO2013166022 A2 WO 2013166022A2 US 2013038880 W US2013038880 W US 2013038880W WO 2013166022 A2 WO2013166022 A2 WO 2013166022A2
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- container
- frozen sample
- bore
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N1/00—Sampling; Preparing specimens for investigation
- G01N1/28—Preparing specimens for investigation including physical details of (bio-)chemical methods covered elsewhere, e.g. G01N33/50, C12Q
- G01N1/286—Preparing specimens for investigation including physical details of (bio-)chemical methods covered elsewhere, e.g. G01N33/50, C12Q involving mechanical work, e.g. chopping, disintegrating, compacting, homogenising
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N35/00—Automatic analysis not limited to methods or materials provided for in any single one of groups G01N1/00 - G01N33/00; Handling materials therefor
- G01N35/00584—Control arrangements for automatic analysers
- G01N35/00722—Communications; Identification
- G01N35/00732—Identification of carriers, materials or components in automatic analysers
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N35/00—Automatic analysis not limited to methods or materials provided for in any single one of groups G01N1/00 - G01N33/00; Handling materials therefor
- G01N35/0099—Automatic analysis not limited to methods or materials provided for in any single one of groups G01N1/00 - G01N33/00; Handling materials therefor comprising robots or similar manipulators
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N35/00—Automatic analysis not limited to methods or materials provided for in any single one of groups G01N1/00 - G01N33/00; Handling materials therefor
- G01N35/00584—Control arrangements for automatic analysers
- G01N35/00722—Communications; Identification
- G01N2035/00891—Displaying information to the operator
- G01N2035/0091—GUI [graphical user interfaces]
Definitions
- the present invention relates generally to machine vision systems and methods, and more particularly to machine vision systems for facilitating control of robotic systems for taking multiple frozen sample cores from frozen samples in containers without thawing the frozen samples.
- Bio samples are commonly preserved to support a broad variety of biomedical and biological research that includes but is not limited to translational research, molecular medicine, and biomarker discovery.
- Biological samples include any samples which are of animal (including human) , plant, protozoal, fungal, bacterial, viral, or other biological origin.
- biological samples include, but are not limited to, organisms and/or biological fluids isolated from or excreted by an organism such as plasma, serum, urine, whole blood, cord blood, other blood-based derivatives, cerebral spinal fluid, mucus (from respiratory tract, cervical) , ascites, saliva, amniotic fluid, seminal fluid, tears, sweat, any fluids from plants (including sap); cells (e.g., animal, plant, protozoal, fungal, or bacterial cells, including buffy coat cells; cell lysates, homogenates, or suspensions; microsomes; cellular organelles (e.g., mitochondria); nucleic acids (e.g., RNA, DNA) , including chromosomal DNA, mitochondrial DNA, and plasmids
- Bio samples may also include plants, portions of plants (e.g., seeds) and tissues (e.g., muscle, fat, skin, etc.).
- Biobanks typically store these valuable samples in containers (e.g., well plates or arrays, tubes, vials, or the like) and cryopreserve them. Tubes, vials, and similar
- containers can be organized in arrays and can be stored in well plates, racks, divided containers, etc. Although some samples are stored at relatively higher temperatures (e.g., about -20 degrees centigrade) , other samples are stored at much lower temperatures. For example some samples are stored in freezers at -80 degrees centigrade, or lower using liquid Nitrogen or the vapor phase above liquid Nitrogen) to preserve the biochemical composition and integrity of the frozen sample as close as possible to the in vivo state to facilitate accurate,
- Biobanks have adopted different ways to address this need to provide sample aliquots.
- One option is to freeze a sample in large volume, thaw it when aliquots are requested and then refreeze any remainder of the parent sample for storage in the cryopreserved state until future aliquots are needed.
- This option makes efficient use of frozen storage space; yet this efficiency comes at the cost of sample quality.
- Exposing a sample repeatedly to freeze/thaw cycles can degrade the sample's critical biological molecules (e.g., RNA) and damage biomarkers, either of which could compromise the results of any study using data obtained from the damaged samples.
- Another option is to freeze a sample in large volume, thaw it when an aliquot is requested, subdivide the remainder of the parent sample in small volumes to make
- the system uses a drill including a hollow coring bit to take a frozen core sample from the original parent sample without thawing the parent sample.
- the frozen sample core obtained by the drill is used as the aliquot for the test. After the frozen core is removed, the remainder of the sample is returned to frozen storage in its original container until another aliquot from the parent sample is needed for a future test .
- One aspect of the invention is a machine vision system for use with a robotic system for taking a plurality of frozen sample cores from frozen samples that are each contained in a respective container.
- the machine vision system includes a platform for supporting one or more of the containers.
- the platform has a station for receiving at least one of the containers and a pair of calibration marks on the platform in fixed positions relative to the station.
- the system has a camera for capturing an image of the container while the container is received at the station.
- a processor is configured to receive image data from the camera indicative of the image of the container.
- the processor is configured to determine one or more locations where a frozen sample core has already been taken from a frozen sample contained in the container by: (a) evaluating contrast in the image to identify one or more bore candidates; and (b) using information about the position of the calibration marks relative to the bore candidates to determine whether or not the one or more candidates are likely to be artifacts instead of real bores in the sample.
- Another aspect of the invention is a method of taking a frozen sample core from a frozen sample that is contained in a container.
- the method includes positioning the container at a station for receiving a container on a platform.
- the platform has a pair of calibration marks on the platform in fixed positions relative to the station.
- An image of the container is captured while the container is received at the station.
- One or more locations where a frozen sample core has already been taken from the frozen sample contained in the container is determined by: (a) evaluating contrast in the image to identify one or more bore candidates; and (b) using information about the position of the calibration marks relative to the bore candidates to determine whether or not the one or more candidates are likely to be artifacts instead of real bores in the frozen sample.
- a frozen sample core is taken from the sample at a location from which no frozen sample core has already been taken, as determined in the determining step.
- Yet another aspect of the invention is a machine vision system for use with a robotic system for taking a plurality of frozen sample cores from frozen samples that are each contained in a respective container.
- the machine vision system includes a platform and a camera for capturing an image of one of the containers while it is on the platform.
- processor is configured to receive image data from the camera indicative of the image captured by the camera.
- the processor is configured to determine one or more locations where a frozen sample core has already been taken from the frozen sample contained in the container by: (a) evaluating contrast in the image to identify one or more bore candidates; and (b)
- Another aspect of the invention is a method of calibrating a robotic system for taking a plurality of frozen sample cores from frozen samples that are each contained in a respective container.
- the method includes using a camera for capturing an image of one or more containers while the
- FIG. 10 Another aspect of the invention is a machine vision system for use with a robotic system adapted for taking a plurality of frozen sample cores from frozen samples that are each contained in a container.
- the machine vision system includes a camera for capturing an image of a container while the container is supported by a platform.
- the camera has an optical axis.
- the system has a ring light for illuminating the container on the platform.
- the ring light includes a plurality of light sources arranged in an annular patter.
- the optical axis of the camera extends through a central portion of the annular pattern.
- a processor is adapted to receive image data from the camera indicative of the image captured by the camera and to determine one or more locations where a frozen sample core has already been taken from the sample contained in the container by evaluating contrast in the image.
- Still another aspect of the invention is a method of determining one or more locations where frozen sample core have already been taken from frozen samples, each of the frozen samples being contained in a respective container.
- the method includes operating a robotic system to move a camera relative to a first one of the containers so the camera is directed at the frozen sample in the first container.
- the frozen sample is illuminated using a ring light.
- the ring light has a plurality of light sources arranged in an annular pattern.
- the camera has an optical axis that extends through a central portion of the annular pattern.
- the camera is used to capture an image of the illuminated frozen sample. Contrast in the captured image is evaluated and the image is processed to identify one or more bore candidates in the captured image and determine whether or not the bore candidates are likely to be artifacts or real bores in the frozen sample.
- the robotic system is operated to move the camera relative to a second of the containers so the camera is directed at the frozen sample in the second container. The imaging is repeated for the frozen sample in the second
- the system includes a camera configured for capturing monochrome images of the containers while the containers are supported by a platform.
- a light is positioned to illuminate the containers and the samples
- a processor is adapted to receive grayscale image data from the camera indicative of images formed by the camera and determine locations where frozen sample cores have already been taken from the samples by evaluating contrast in the images.
- the light emits light having a color other than white.
- Another aspect of the invention is a method of determining one or more locations where frozen sample core have already been taken from frozen samples.
- Each of the frozen samples is contained in a respective container. The method includes operating a robotic system to move a camera relative to a first one of the containers so the camera is directed at the frozen sample in the first container.
- the frozen sample is illuminated with a colored light.
- the camera is used to capture a grayscale image of the illuminated frozen sample.
- Contrast in the captured image is evaluated and the image is processed to identify one or more bore candidates in the captured image and determine whether or not the bore candidates are likely to be artifacts or real bores in the frozen sample.
- the robotic system is operated to move the camera relative to a second of the containers so the camera is directed at the frozen sample in said second container. The imaging is repeated for the frozen sample in the second container.
- Another aspect of the invention is a machine vision system for use with a robotic system for taking a plurality of frozen sample cores from frozen samples that are each contained in a container.
- the system includes a camera for taking images of the containers while the containers are supported by a platform.
- a light is positioned to illuminate the containers and the samples contained therein while the containers are on the platform.
- the light has red light emitting elements, blue light emitting elements, and green light emitting elements.
- the intensity of light emitted from the red, blue, and green light emitting elements is selectively adjustable to allow any of multiple different colors of light to be selected as the color of light to be emitted by the light.
- a processor is adapted to receive image data from the camera indicative of images formed by the camera and determine locations where frozen sample cores have already been taken from the samples by evaluating contrast in the images.
- the processor is adapted to receive input about the color of the samples in the containers and adjust the color of the light emitted by the light to reduce a difference between the color of the samples and the color of the light emitted by the light.
- Another aspect of the invention is a method of determining one or more locations where frozen sample core have already been taken from frozen samples.
- Each of the frozen samples is contained in a respective container.
- the method includes operating a robotic system to move a camera relative to a first one of the containers so the camera is directed at the frozen sample in the first container.
- the frozen sample is illuminated with a colored light. The color of the light is selected to match the color of the frozen sample.
- the camera is used to capture an image of the illuminated frozen sample.
- Contrast in the captured image is evaluated and the image is processed to identify one or more bore candidates in the captured image and determine whether or not the bore candidates are likely to be artifacts or real bores in the frozen sample.
- the robotic system is operated to move the camera relative to a second of the containers so the camera is directed at the frozen sample in said second container.
- the imaging process is repeated for the frozen sample in the second container.
- Yet another embodiment of the invention is a method of determining one or more locations where frozen sample core have already been taken from frozen samples. Each of the frozen samples is contained in a respective container. The method includes operating a robotic system to position one of the containers on a platform at a station for receiving the
- a container while a frozen sample core is extracted from the frozen sample contained in the container.
- a light is used to provide at least one of back lighting and side lighting for the container.
- a camera is used to capture an image of the frozen sample while illuminated by the light. Contrast in the captured image is evaluated and the image is processed to identify one or more bore candidates in the captured image.
- FIG. 1024 Another inventive aspect is a machine vision system for use with a robotic system adapted for taking a plurality of frozen sample cores from frozen samples that are each contained in a container.
- the machine vision system includes a camera for capturing an image of a container while the container is supported by a platform at a station for receiving the container while a frozen sample core is extracted from the frozen sample contained therein.
- the system has a red light for illuminating the container from above while it is on the platform at the station with substantially monochromatic red light.
- a processor is adapted to receive image data from the camera indicative of the image captured by the camera and to determine one or more locations where a frozen sample core has already been taken from the sample contained in the container by evaluating contrast in the image .
- Yet another aspect of the invention is a method of determining one or more locations where a frozen sample core have already been taken from frozen samples.
- Each of the frozen samples is contained in a respective container.
- the method includes operating a robotic system to position one of the containers on a platform at a station for receiving the container while a frozen sample core is extracted from the frozen sample contained in the container.
- the container is illuminated from above while it is on the platform at the station with substantially monochromatic red light.
- a camera is used to capture an image of the frozen sample while illuminated by the red light. Contrast in the captured image is evaluated and the image is processed to identify one or more bore
- FIG. 10 Another aspect of the invention is a machine vision system for use with a robotic system for taking a plurality of frozen sample cores from frozen samples that are each contained in a respective container.
- the machine vision system includes a platform for supporting one or more of the containers. The platform having a station for receiving at least one of the containers .
- the system has a camera for capturing an image of the container while the container is received at the station.
- a processor is configured to receive image data from the camera indicative of the image of the container.
- the processor is configured to determine one or more locations where a frozen sample core has already been taken from a frozen sample
- the container by evaluating contrast in the image to identify one or more bore candidates and identify an edge of the container and using information about the position of the edge relative to the bore candidates to determine whether or not the one or more candidates are likely to be artifacts instead of real bores in the sample.
- Another aspect of the invention is a method of determining one or more locations where a frozen sample core have already been taken from frozen samples. Each of the frozen samples is contained in a respective container. The method includes operating a robotic system to position one of the containers on a platform at a station for receiving the
- a container while a frozen sample core is extracted from the frozen sample contained in the container.
- a camera is used to capture an image of the frozen sample. Contrast in the captured image is evaluated to identify one or more bore candidates and identify an edge of the container. Information about the position of the edge relative to the bore candidates is used to determine whether or not the one or more candidates are likely to be artifacts instead of real bores in the sample.
- One aspect of the invention is a machine vision system for use with a robotic system for taking a plurality of frozen sample cores from frozen samples that are each contained in a respective container.
- the machine vision system includes a platform for supporting one or more of the containers.
- the platform has a station for receiving at least one of the containers.
- the system includes a camera for capturing an image of the container while the container is received at the station.
- the system includes a fill level detection system adapted to detect the positions of the surfaces of the frozen samples.
- a processor is configured to receive signals from the fill level detection system and use the signals to determine where to position the camera to obtain an image of the frozen samples.
- Yet another aspect of the invention is a machine vision system for use with a robotic system for taking a plurality of frozen sample cores from frozen samples that are each contained in a respective container.
- the machine vision system includes a platform for supporting one or more of the containers .
- the platform has a station for receiving at least one of the containers.
- the system includes a coring probe for taking frozen sample cores from the frozen samples.
- the system includes a camera for capturing an image of the container while the container is received at the station.
- a processor is configured to receive image data from the camera indicative of the image of the container and to determine one or more
- the processor is configured to move the coring probe into the open end of at least one bore to clear the open end of the bore of debris.
- Another aspect of the invention is a method of taking a frozen sample core from a frozen sample that is contained in a container.
- the method includes positioning the container at a station for receiving a container on a platform. An image of the container is captured while the container is received at the station. One or more locations where a frozen sample core has already been taken from the frozen sample contained in the container is determined. The frozen sample core is taken from the frozen sample at a location from which no frozen sample core has already been taken, as determined in the determining step. After taking the frozen sample core from the frozen sample, a coring probe is inserted into the one or more locations where a frozen sample core has been taken to clear the one or more locations where a frozen sample core has been taken of debris.
- Still another aspect of the invention is a machine vision system for use with a robotic system adapted for taking a plurality of frozen sample cores from frozen samples that are each contained in a container.
- the machine vision system includes a camera for capturing an image of a container while the container is supported by a platform.
- the system includes a light for illuminating the container on the platform.
- a majority of the light energy emitted by the light is selected from the group consisting of red light with a wavelength in the range of 620nm to 750nm and green light with a wavelength in the range of 495nm to 570nm.
- a processor is adapted to receive image data from the camera indicative of the image captured by the camera and to determine one or more locations where a frozen sample core has already been taken from the sample contained in the container by evaluating the image.
- Another aspect of the invention is a method of determining one or more locations where frozen sample core have already been taken from frozen samples, each of the frozen samples being contained in a respective container.
- the method includes operating a robotic system to move a camera relative to a first one of the containers so the camera is directed at the frozen sample in the first container.
- the frozen sample is illuminated using a light, wherein a majority of the light energy emitted by the light is selected from the group
- the image is used to identify one or more bore candidates in the captured image and determine whether or not the bore candidates are likely to be artifacts or real bores in the frozen sample.
- the robotic system is operated to move the camera relative to a second of the containers so the camera is directed at the frozen sample in said second
- the imaging is repeated for the frozen sample in said second container.
- FIG. 1 is perspective of one example of a frozen aliquotter including one embodiment of a machine vision system of the present invention
- FIG. 2 is a top plan of the frozen aliquotter
- FIG. 3 is a top plan of the frozen aliquotter with parts removed to avoid obstructing view of one embodiment of a platform thereof;
- FIG. 4 is an enlarged perspective of the platform taken in a plane including line 4--4 on Fig. 4
- FIG. 5 is a perspective of a fragment of the frozen aliquotter shown in cross section taken in a plane including line 5--5 on Fig. 2;
- FIG. 6 is a perspective of one embodiment of robotic end effector for use with a frozen aliquotter
- FIG. 7 is a bottom plan view of the robotic end effector illustrated in Fig. 6;
- FIG. 8 is a schematic diagram showing some of the components of the frozen aliquotter
- FIG. 9 is a schematic diagram illustrating bore candidates that differ in size
- FIG. 10 is a schematic diagram illustrating one embodiment of a geometric pattern according to which frozen sample cores are extracted from a frozen sample
- FIG. 12 is a schematic diagram illustrating bore candidates that are positioned at various different angles relative to one another from a center of the container;
- FIG. 13 is a schematic diagram illustrating bore candidates that do not follow an expected sequence planned for extraction of frozen sample cores from a frozen sample;
- FIG. 14 is a photograph of a container illustrating use of an edge finding algorithm to identify the location of an edge of the container from the image data;
- FIG. 15 is a schematic diagram illustrating one embodiment of using fixed calibration marks to identify the location of features in the image data
- FIG. 16 is a photograph showing a pair of
- FIG. 17 is a photograph of one embodiment of a density step target
- Figure 19 is a schematic illustration of the coring probe of FIG. 18 inserted into the bore.
- the source container station 107 includes a receptacle 106 for receiving containers 105 and a pair of clamping jaws 108, 110 on opposite sides at the top of the receptacle. At least one of the jaws 108 is selectively moveable, such as by a pneumatic actuator (not shown), toward and away from the other jaw 110 for selectively clamping containers 105 in position at the station 107 to hold them in place during extraction of a frozen sample and releasing the containers so they can be removed from the station and replaced in the tray 117 afterward. Similar jaws can be used to hold the container 105 at the sample receiving station 109 if desired .
- the system could be adapted for use with well plates and arrays in which multiple different frozen samples are stored in a single container.
- appropriate components can be provided (e.g., on the end effector) for moving well plates or arrays instead of individual containers and the stations 107, 109 for receiving the containers can be adapted to receive well plates or arrays without departing from the scope of the invention.
- the clamping system can be adapted to hold well plates and arrays within the scope of the invention.
- a cooling system 131 for keeping the frozen samples and the frozen sample cores extracted therefrom frozen is positioned under the platform 103 in the illustrated embodiment, although the cooling system can be positioned elsewhere and/or other cooling systems used without departing from the scope of the invention.
- the end effector 111 of the robotic system 101 includes a sample coring probe 121 and a sample core extraction system 123 operable to move the sample coring probe into one of the frozen samples contained in one of the containers 105 and then withdraw the coring probe from the frozen sample to obtain a frozen sample core from the frozen sample.
- the sample core extraction system 123 includes a motor 125 adapted to rotate the sample coring probe 123 as the robotic drive system 113 lowers the sample coring probe into the container and then raises it out of the container. Additional details about the operation of a coring probe to extract frozen sample cores from frozen samples are set forth in U.S. pre-grant publication No. 20090019877, PCT application No. PCT/US2011/61214 , filed
- any sample coring probe and sample extraction system can be used within the scope of the invention, as long as they can be operated to extract a frozen sample core from a frozen sample while resulting in only limited to no thawing of the frozen sample material and the frozen sample core extracted therefrom .
- the end effector 111 also includes a gripping system 127 operable to selectively hold and release containers 105 for use by the robotic system 101 in moving containers back and forth between the trays 117 and the stations 107, 109 on the platform for the containers from which frozen sample cores are being taken and into which frozen sample cores are being deposited.
- a gripping system 127 operable to selectively hold and release containers 105 for use by the robotic system 101 in moving containers back and forth between the trays 117 and the stations 107, 109 on the platform for the containers from which frozen sample cores are being taken and into which frozen sample cores are being deposited.
- the gripping system includes a plurality of moveable fingers 129 moveable by one or more pneumatic actuators (not shown) under the control of the processor 114. It is understood other gripping systems may be used within the scope of the invention.
- the gripping system can be modified if desired to facilitate use of the gripping system to move well plates or arrays containing multiple frozen samples.
- the processor 114 suitably processes the image captured while the container 105 is illuminated with the light 145 in various ways to facilitate this determination.
- the processor 114 is configured to perform a thresholding filter to the raw image data, apply one or more morphological filters (e.g., erosion, dilation, opening, and/or closing) to the thresholded image, and then apply particle analysis to identify one or more bore candidates.
- morphological filters e.g., erosion, dilation, opening, and/or closing
- first line extending between the bore and the center axis of the container and the second line extending between the center axis of the container and another bore
- the number of bores in the geometric pattern can vary within the scope of the invention.
- the pattern in Fig. 10 is a regular pattern, meaning the bores are all the same size, are all spaced the same distance from the center, and are all spaced at equal angles, it is understood that the pattern could be irregular within the scope of the invention.
- some bore candidates can be spaced too close to the center (e.g., see distance D4 in Fig. 11) or too far from the center of the container (e.g., see distance D5 in Fig. 11), or conversely, spaced to far or close to the edge of the container if the edge of the container can be detected, to fall within the geometric pattern.
- the angular spacing between one or more of the bore candidates can be different (either too high ⁇ 2 or too low ⁇ 3) from the expected angular spacing.
- frozen sample cores will be extracted from the frozen samples according to a specific orderly
- the processor 114 can determine a bore candidate is an artifact on the basis that it is out of order with a sequence according to which frozen sample cores are expected to be extracted from the frozen sample, particularly when multiple bore candidates 301, 303 follow the expected sequence and only one bore candidate 305 is out of sequence .
- the processor 114 can apply more rigorous standards to help exclude likely artifacts when the number of bore candidates is too high.
- the circles 163, 165 define an area to be scanned in an attempt to identify the edge of the container 105.
- the processor 114 is suitably configured to evaluate the image data to determine points 169 along each line where there is sharp contrast. Each point 169 potentially represents an intersection between the edge of the container 105 and the respective scan line 167. In the case of a successful attempt to identify the edge of a container, a significant number of the points 169 will lie on the same circle (or other shape if the containers do not have circular shapes) in which case the processor 114 concludes the points 169 lying thereon define the edge of the container 105.
- the edge of the container can refer to the edge of a well or other discrete area within which one frozen sample is stored on a well plate or other container adapted for holding multiple different samples .
- Ultraviolet or infrared lighting can help enhance the contrast between the edge of the container and the surroundings in the image. This enhanced contrast improves detection and
- a separate UV or IR light source can be positioned to illuminate the container.
- the UV or IR light source can be moveable (e.g., mounted on the end effector 111) or fixed (e.g., secured to or within the platform 103) within the scope of the invention.
- the separate UV or IR light source can be positioned in the platform to provide indirect lighting (e.g., backlighting or side lighting) to the container to aid in edge detection.
- any one of or combination of the lights 145, 181, 183, 185 can include a UV or IR light source .
- the processor 114 is suitably configured to use the calibration marks 161 (e.g., in combination with edge detection or without edge detection) to determine whether or not the one or more bore candidates are likely to be artifacts instead of real bores in the frozen sample.
- the calibration marks 161 are designed to ensure there is strong color contrast between the calibration marks and the surrounding objects in the image even if there is frost formation or other conditions that minimize contrast between the edge of the container 105 and its
- the processor 114 can determine the position of the bore candidates by comparing their positions to the positions of the calibration marks.
- the calibration marks 161 are suitably positioned to form a triangle with the center of the container.
- the processor 114 can be configured to identify the center axis of the container by triangulating the center from the calibration marks.
- a machine vision system 141 including a processor 114 that is configured to use calibration marks 161 to identify the center of a container is not sensitive to errors in the rotation of the camera or to errors in translation of the camera.
- the processor 114 can be configured to identify the edge of the container 105 and/or the center axis of the
- the processor 114 can be configured to both use the calibration marks and peripheral edge detection to identify the center of the container.
- the processor 114 can be configured to compare the positions of the bore candidates directly to the positions of the calibration marks 161 to determine which bore candidates are likely to be artifacts without computing the relative distances between the bore candidates and the center of the container or the edge of the container without computing the center of the container and/or without computing the edge of the container .
- the processor 114 is configured to automatically select a suitable location in the frozen sample from which the robotic system 101 can take another frozen sample core (or in the case of a frozen sample from which no frozen sample cores have been taken yet, it is configured to automatically select the location from which the initial frozen sample core will be extracted) once the processor has determined from the image data whether or not there are any bores in a particular frozen sample and the locations of any such bores.
- This facilitates taking frozen sample cores from samples that may have already been subjected to previous extractions of frozen sample cores without requiring the processor 114 to have access to any information about the number of previous frozen sample cores that may have been extracted from the sample or the locations within the frozen sample from which any such sample cores have been taken. This eliminates the need for manual intervention to orient the containers 105 is a particular way and greatly reduces the amount of data on a sample that needs to be tracked to
- the system 101 can still recognize bores in the frozen sample even if the bores are not where they would be expected to be if the previously extracted frozen sample cores had been extracted according to the protocols of the system 101 instead of whatever other protocols were previously in use.
- the processor 114 can be configured to select a location for the next frozen sample core that continues the geometric pattern that has already been started. Another option if it is desired that the next sample core be taken from a particular radial location in the frozen sample is that the processor 114 can be configured to select a location that is the desired radial distance from the center of the container and also sufficiently spaced from existing bores in the frozen sample. The processor 114 can be configured so a user can select which of these options is used for any
- the processor 114 is also configured to select an appropriate initial geometric pattern for the locations from which a plurality of frozen sample cores will be extracted if the processor determines there are no existing bores in the frozen sample.
- the processor 114 can be configured to select a geometric pattern that maximizes the number of frozen sample cores that can be taken from the frozen sample and/or the processor can be configured to select a geometric pattern that results in one or more frozen sample cores (e.g., all frozen sample cores) being taken from a particularly desired radial distance from the center of the container.
- the processor 114 can be configured to allow a user to select which of several different strategies will be used for planning the geometric pattern of the locations from which frozen sample cores are to be extracted for different containers or sets of containers. If desired, the processor 114 can be configured to display the geometric pattern selected by the processor and/or the
- the color of light emitted by the light 145 can be important. In general, better results are obtained when the light used to illuminate the frozen sample matches the color of the frozen sample.
- the color of the light used to illuminate the frozen sample is suitably the same as the color of the sample or no more different from the color of the sample than one of the two adjacent colors on an RGB color wheel having six colors arranged in the following order extending around the wheel: red, yellow, green, cyan, blue, magenta, and then back to red.
- a red light works well with red samples, orange samples, and yellow samples.
- the light 145 can emit red light for illuminating the frozen sample. It is also anticipated that it will be desirable in some cases for the light to emit green light or blue light. However, the light can emit any color light within the broad scope of the invention .
- the light 145 includes red light emitting elements, blue light emitting elements, and green light emitting elements and the intensity of light emitted from the red, blue, and green light emitting elements is selectively adjustable to allow any of multiple different colors of light to be selected as the color of light that is used to illuminate the samples.
- the light 145 includes red light emitting elements that emit red light having a wavelength in the range of about 620nm to about 750nm (about 400THz to about 484THz) .
- the majority of the light energy emitted by the light is suitably within the range of about 620nm to about 750nm.
- the processor suitably adjust the color of the light used to illuminate the sample to white when capturing the image that will be used to determine the color of the sample to facilitate accurate color detection and then adjusts the color of the light to match the color of the sample.
- the processor can be configured to capture a color image of one of the samples to assess the color of all of the samples in that set and adjust the color once to match the color of all the samples in the set.
- Digital cameras are available that can capture both grayscale images and color images, so it is possible that the camera captures one or more color images (e.g., to identify the color of the sample so the light used to illuminate the sample can be adjusted to match the color of the sample) and also captures grayscale images for use by the processor to identify locations where bores exist within the frozen samples.
- the machine vision system 141 is suitably a
- the platform 103 has one or more fixed targets 171 positioned thereon.
- the camera 143 is mounted on the robotic system 101 so it can be moved to capture an image of each of the fixed targets 171.
- the processor is suitably configured to receive image data from the camera indicative of images of the target (s) formed by the camera and calibrate the robotic system 101 using an image of the one or more fixed targets 171 on the platform 103. As illustrated in Fig.
- At least one of the targets 173 has an image (e.g., a cross hair) having a point or intersection of lines for calibration in the x and y directions and a shape (e.g., circle) having a known size for calibration in the z direction.
- the calibration system suitably has a user interface (not shown) configured to allow a user to guide the camera from a position that is not in registration with one of the targets (e.g., so a reticule overlaying the captured image is not aligned with the cross hair) toward a position that is in registration with said target (e.g., so the reticule is aligned with the cross hair) .
- the processor 114 is suitably configured to use multiple additional features on the platform 103 as targets to help calibrate the robotic system 101.
- the platform 103 is suitably configured to use multiple additional features on the platform 103 as targets to help calibrate the robotic system 101.
- the processor 114 is suitably configured to use multiple additional features on the platform 103 as targets to help calibrate the robotic system 101.
- processor 114 is suitably configured to calibrate the robotic system 101 using images of multiple features on the platform 103 selected from the group consisting of:
- Fig. 3 illustrates 13 calibration points that can be used according to one particular embodiment of the calibration system, with each of calibration points being labeled consecutively from 201-213.
- Point 201 corresponds to the target 175 on the platform 103 in the recessed area 115.
- Points 201, 202, and 203 correspond to the stations 107, 109 for receiving the containers 105 and the station 119 for washing the coring probe 121, respectively.
- Points 204-208 correspond to various points (e.g., points at the corners) of one of the trays 117a and points 209-212 correspond to various points (e.g., points at the corners) of another of the trays 117b.
- the image data from the camera 143 is used to instruct the robotic drive system (either by the processor or a user) to raise or lower the camera until the size of the shape in the image captured by the camera indicates the camera is the proper distance from the target in the z- direction.
- Calibration in the Z-direction could instead be achieved using a lens setting for the camera 143 having a known focal length and then adjusting the height of the camera until the image is in focus.
- the processor When the camera 143 is in registration with the target 171 and the correct distance from the target, the processor records positional information from the robotic system 101 (e.g., data from encoders and other devices that provide positional feedback about the position of various components of the robotic system) and designates that
- the station 109 for receiving the container 105 in which a frozen sample core is to be deposited;
- the calibration targets 171 and calibration points include each of points 201- 213 on Fig. 3.
- the density step target 177 is also used during the calibration process to adjust camera settings and light
- the light 145 is turned on and the diaphragm of the camera 143 and/or intensity of electric current supplied to the light are adjusted while the camera captures images of the density step target 177 until a particular shaded block on the density step target is read as a certain gray level by the camera 143. For example, good results have been obtained when the light 145 and camera 143 are adjusted so the third lightest color block on a standard density step target is read by the camera as 200 gray level .
- the user adjusts the position of the end effector until the gripper system 127 is in registration with the target 171 or other reference point and provides an indication to the processor that the gripper system is in registration therewith.
- the order in the steps of this method is not important.
- the processor 114 determines the positional offset between the camera 143, coring prove 121, and gripper assembly 127 using the information provided in this process.
- the entire calibration process is suitably completed without requiring any contact between the end effector 111 or any components moveable with the end effector and the platform 103 or any components on the platform.
- a set of containers 105 containing frozen samples is placed on the platform 103.
- one or more trays 117a can be loaded with sample containers 105 and then placed on the platform 103 (e.g., in the recessed area 115) .
- a set of empty containers 105 for receiving frozen sample cores after they are extracted is loaded into one or more additional trays 117b and placed on the platform 103.
- the robotic system 101 uses the gripper system 127 to move one of the containers 105 containing a frozen sample to the station 107 for receiving containers from which frozen sample cores are being extracted and moves one of the empty containers to the station 109 for receiving
- the robotic system moves the camera 143 into position over the station 107 for holding the containers 105 containing frozen sample while frozen sample cores are extracted from them.
- the robotic system suitably includes a fill level detection system for detecting the level of an upper surface of the frozen sample. Details concerning the construction and operation of a suitable fill level detection system are provided in U.S. Application No. 13/359,301, entitled Robotic End
- the fill level detection system provides information about the position of the upper surface of the frozen sample.
- the fill level detection system can be used to position the camera 143 at a desired level above the frozen sample to improve focusing of the camera.
- the processor 114 uses the information from the fill level detection system about the position of the upper surface of the frozen sample to determine the elevation at which to position the camera for obtaining an image of the frozen sample taken while the camera is within an optimal range of distances from the upper surface of the sample.
- the light 145 is used to illuminate the container 105 at the station 107 and the frozen sample contained therein.
- the machine vision system 141 includes the option of adjusting the color of the light 145, the color of the frozen sample is determined (e.g., using image data from the camera and/or user input) and the color of the light is adjusted to match the color of the frozen sample, as described above. For example, if the frozen sample is red, orange, or yellow, the light 145 can be adjusted to emit red light. Likewise, if additional lighting options are used, additional images of the container 105 are captured with one or more of the lights 181, 183, 185 providing illumination.
- a thresholding filter is suitably applied to the raw image obtained with illumination from light 145.
- a morphological filter is also applied to the image. After the image has been filtered a particle analysis imaging
- the processor uses the image data to evaluate whether or not any bore candidates are actual bores or just artifacts in order to determine whether or not any frozen sample cores have already been taken from the frozen sample and, if so, to identify the location (s) from which they were taken.
- the method suitably includes heating the calibration marks using the low-power resistance heaters to ensure the calibration marks are not obscured by frost.
- the processor 114 Once the processor 114 has identified the bore candidates and determined which bore candidates are likely to be artifacts and which are likely to be real bores, the processor automatically selects a position from which a frozen sample core will be extracted, accounting for the position of pre-existing bores in the frozen sample if there are any. Then the processor 114 instructs the robotic system 101 to move the coring probe 121 into position over the selected location and instructs the sample extraction system to extract a frozen sample core from the location.
- the frozen parent sample is further processed to clear away any frost crystals or other debris in each of the bores in the frozen sample to ensure better accuracy and reliability in the machine vision system 141 when the sample is retrieved again later from frozen storage to obtain additional frozen sample cores.
- the bores may contain or be obscured by frost crystals that have grown on the sample (e.g., while the sample was in frozen storage), by debris (e.g., from previously drilling frozen sample cores), and/or for other reasons.
- the processor 114 suitably uses the image data that was obtained from the sample before the most recent frozen sample core was extracted (i.e., the image data used to evaluate bore
- the processor 114 suitably also uses data obtained during the extraction of the most recent frozen sample core (e.g., the geometric sampling pattern used to obtain the most recent frozen sample core(s), information about the location from which the most recent frozen sample cores were taken) . Using this image data about the location (s) of any bores before the most recent extraction and the data about the location (s) of any bores made during the most recent extraction, the processor 114 determines the location (s) of every bore and suspected bore in the frozen sample.
- data obtained during the extraction of the most recent frozen sample core e.g., the geometric sampling pattern used to obtain the most recent frozen sample core(s), information about the location from which the most recent frozen sample cores were taken
- the processor 114 instructs the robotic system to reprocess or clean any bore(s) made during the most recent frozen sample core extraction, and then
- the processor 114 subsequently instructs the robotic system to reprocess or clean any bore(s) identified using the image data that was obtained before the most recent frozen sample core was extracted.
- the processor 114 instructs the robotic system to reprocess or clean only any bore(s) identified using the image data that was obtained before the most recent frozen sample core was extracted.
- the processor 114 instructs the robotic system to reprocess or clean only any bore(s) made during the most recent frozen sample core
- the processor 114 instructs the robotic system to reprocess or clean any bore(s) identified using the image data that was obtained before the most recent frozen sample core was extracted prior to
- the processor 114 may direct an ejector pin 190 of the end effector 111 to move to an extended position in which the ejector pin extends from a distal end of the coring probe 121.
- the coring probe 121 is positioned over an identified bore 192 (Fig. 18) and then lowered into the bore to clear the bore of any debris (Fig. 19) .
- the coring probe 121 is lowered into the identified bore 192 whether or not there is debris in the bore.
- the machine vision system 141 can include sensors as described in U.S. Application No. 13/359,301, filed January 26, 2012, to determine whether or not the ejector pin 190 is being lowered into a bore instead of being lowered into contact with frozen sample. As the ejector pin 190 enters the open end of the bore, any frost, debris or other similar objects that may be
- obstructing the view of the bore is knocked away from the open end of the bore, either by being knocked into the bottom of the bore or by being pushed aside. Clearing the bore(s) of debris and frost makes it easier for the machine vision system 141 to correctly identify bores in a frozen sample next time it is retrieved from frozen storage when additional frozen sample cores are required. Because the coring probe and ejector pin 190 are already required to contact the sample to complete other parts of the process, there is substantially no added risk of contaminating the sample by using the coring probe and ejector pin to clear the debris away from the open ends of the bores.
- aspects of the invention may also be practiced in distributed computing environments where tasks are performed by local and remote processing devices that are linked (either by hardwired links, wireless links, or by a combination of
- program modules may be located in both local and remote memory storage devices .
- the computer may also include a magnetic hard disk drive for reading from and writing to a magnetic hard disk, a magnetic disk drive for reading from or writing to a removable magnetic disk, and an optical disk drive for reading from or writing to removable optical disk such as a CD-ROM or other optical media.
- the magnetic hard disk drive, magnetic disk drive, and optical disk drive are connected to the system bus by a hard disk drive interface, a magnetic disk drive-interface, and an optical drive interface, respectively.
- the drives and their associated computer-readable media provide nonvolatile storage of computer-executable instructions, data structures, program modules, and other data for the computer.
- exemplary environment described herein employs a magnetic hard disk, a removable magnetic disk, and a removable optical disk
- other types of computer readable media for storing data can be used, including magnetic cassettes, flash memory cards, digital video disks, Bernoulli cartridges, RAMs, ROMs, and the like.
- Program code means comprising one or more program modules may be stored on the hard disk, magnetic disk, optical disk, ROM, and/or RAM, including an operating system, one or more application programs, other program modules, and program data.
- a user may enter commands and information into the computer through keyboard, pointing device, or other input devices, such as a microphone, joy stick, game pad, satellite dish, scanner, or the like.
- These and other input devices are often connected to the processing unit through a serial port interface coupled to system bus.
- the input devices may be connected by other interfaces, such as a parallel port, a game port, or a universal serial bus (USB) .
- a monitor or another display device is also connected to system bus via an interface, such as video adapter.
- personal computers typically include other peripheral output devices (not shown), such as speakers and printers.
- the computer may operate in a networked environment using logical connections to one or more remote computers, such as remote computers .
- Remote computers may each be another personal computer, a server, a router, a network PC, a peer device or other common network node, and typically include many or all of the elements described above relative to the computer.
- the logical connections include a local area network (LAN) and a wide area network (WAN) that are presented here by way of example and not limitation.
- LAN local area network
- WAN wide area network
- Such networking environments are commonplace in office-wide or enterprise-wide computer networks, intranets and the Internet.
- the computer When used in a LAN networking environment, the computer is connected to the local network through a network interface or adapter.
- WAN networking When used in a WAN networking
- the computer may include a modem, a wireless link, or other means for establishing communications over the wide area network, such as the Internet.
- the modem which may be internal or external, is connected to the system bus via the serial port interface.
- program modules depicted relative to the computer, or portions thereof, may be stored in the remote memory storage device. It will be appreciated that the network connections shown are exemplary and other means of establishing communications over wide area network may be used.
- Such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage, or other magnetic storage devices, or any other medium that can be used to carry or store desired program code means in the form of computer-executable instructions or data structures and that can be accessed by a general purpose or special purpose computer.
- a network or another communications connection either hardwired, wireless, or a combination of hardwired or wireless
- the computer properly views the connection as a computer-readable medium.
- any such a connection is properly termed a computer-readable medium.
- Computer-executable instructions comprise, for example, instructions and data which cause a general purpose computer, special purpose computer, or special purpose
- processing device to perform a certain function or group of functions .
- a frozen sample that is contained in a container 105 is positioned (e.g., by the robotic system) at the station 107 on the platform 103 having
- processor 114 uses the captured image to determine one or more locations where a frozen sample core has already been taken from the frozen sample contained in the container by: (a) evaluating contrast in the image to identify one or more bore candidates; and (b) determining whether or not the one or more bore
- the processor 114 uses information including at least one of the following:
- the distance between the bore candidate and a center axis of the container 105 ; the angle formed between a first line and a second line, the first line extending between the bore and the center axis of the container and the second line extending between the center axis of the container and another bore
- the system takes a frozen sample core from the frozen sample at a location from which no frozen sample core has already been taken, as determined by the processor.
- the robotic system 101 is calibrated by using the camera 143 to capture an image of one or more fixed targets 171 on the platform 103.
- the processor 114 uses an image of the one or more targets 171 to calibrate the robotic system.
- the same camera 143 is used to capture an image of one or more containers 105 while the containers are supported by the platform to determine whether or not one or more frozen sample cores has already been taken from the frozen sample .
- the robotic system 101 is operated to move the camera 143 relative to a first one of the containers 105 so the camera is directed at the frozen sample in the first container.
- the frozen sample in the container 105 is illuminated using the ring light 145.
- the camera 143 is used to capture an image of the illuminated frozen sample.
- the processor 114 evaluates contrast in the captured image and processes the image to identify one or more bore candidates in the captured image.
- the processor 114 determine whether or not the bore candidates are likely to be artifacts or real bores in the frozen sample.
- the robotic system 101 moves the camera relative to a second of the containers 105 so the camera is directed at the frozen sample in the second container and the process is repeated.
- the robotic system 101 moves the camera 143 relative to a first one of the
- the robotic system 101 moves the camera 143 relative to a second of the containers 105 so the camera is directed at the frozen sample in the second container. The process is repeated.
- the robotic system 101 moves the camera 143 relative to a first one of the containers 105 so the camera is directed at the frozen sample in the first container.
- the frozen sample in the container 105 is illuminated with a light 145 that has a color selected to match the color of the frozen sample.
- the camera 143 captures an image of the illuminated frozen sample.
- the processor 114 evaluates contrast in the captured image and processes the image to identify one or more bore candidates in the captured image.
- the processor 114 determines whether or not the bore candidates are likely to be artifacts or real bores in the frozen sample.
- the robotic system moves the camera 143 relative to a second of the containers 105 so the camera is directed at the frozen sample in the second container and the process is repeated.
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- Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Analytical Chemistry (AREA)
- Pathology (AREA)
- Engineering & Computer Science (AREA)
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Abstract
Description
Claims
Priority Applications (6)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
BR112014026936A BR112014026936A2 (en) | 2012-04-30 | 2013-04-30 | machine vision system for use with a robotic system for taking a plurality of frozen sample cores from frozen samples that are contained in a respective container, and methods for calibrating a robotic system for taking a plurality of frozen cores. frozen sample from frozen samples that are contained in a respective container, taking a frozen sample core from a frozen sample that is contained in a container and determining one or more locations where frozen sample cores have already been taken from frozen samples |
EP13724056.0A EP2845013A2 (en) | 2012-04-30 | 2013-04-30 | Machine vision system for frozen aliquotter for biological samples |
AU2013256489A AU2013256489A1 (en) | 2012-04-30 | 2013-04-30 | Machine vision system for frozen aliquotter for biological samples |
CN201380022571.9A CN104428678A (en) | 2012-04-30 | 2013-04-30 | Machine vision system for frozen aliquotter for biological samples |
JP2015510387A JP6108572B2 (en) | 2012-04-30 | 2013-04-30 | Machine vision system for frozen aliquoters for biological samples |
CA2870505A CA2870505A1 (en) | 2012-04-30 | 2013-04-30 | Machine vision system for frozen aliquotter for biological samples |
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US201261640662P | 2012-04-30 | 2012-04-30 | |
US61/640,662 | 2012-04-30 | ||
US13/489,234 US20130286192A1 (en) | 2012-04-30 | 2012-06-05 | Machine Vision System for Frozen Aliquotter for Biological Samples |
US13/489,234 | 2012-06-05 | ||
US13/844,156 | 2013-03-15 | ||
US13/844,156 US20140267713A1 (en) | 2013-03-15 | 2013-03-15 | Machine Vision System for Frozen Aliquotter for Biological Samples |
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WO2013166022A2 true WO2013166022A2 (en) | 2013-11-07 |
WO2013166022A3 WO2013166022A3 (en) | 2014-03-13 |
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PCT/US2013/038880 WO2013166022A2 (en) | 2012-04-30 | 2013-04-30 | Machine vision system for frozen aliquotter for biological samples |
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EP (1) | EP2845013A2 (en) |
JP (1) | JP6108572B2 (en) |
CN (1) | CN104428678A (en) |
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BR (1) | BR112014026936A2 (en) |
CA (1) | CA2870505A1 (en) |
WO (1) | WO2013166022A2 (en) |
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US20090019877A1 (en) | 2006-01-13 | 2009-01-22 | Dale Larson | Systems, Methods and Devices for Frozen Sample Distribution |
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US20040085443A1 (en) * | 2000-12-13 | 2004-05-06 | Kallioniemi Olli P | Method and system for processing regions of interest for objects comprising biological material |
US8068988B2 (en) * | 2003-09-08 | 2011-11-29 | Ventana Medical Systems, Inc. | Method for automated processing of digital images of tissue micro-arrays (TMA) |
DK1756545T3 (en) * | 2004-06-18 | 2011-12-19 | Covance Inc | Frozen tissue microarray |
US7405056B2 (en) * | 2005-03-02 | 2008-07-29 | Edward Lam | Tissue punch and tissue sample labeling methods and devices for microarray preparation, archiving and documentation |
US9533418B2 (en) * | 2009-05-29 | 2017-01-03 | Cognex Corporation | Methods and apparatus for practical 3D vision system |
US8744163B2 (en) * | 2010-02-09 | 2014-06-03 | International Genomics Consortium | System and method for laser dissection |
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2013
- 2013-04-30 AU AU2013256489A patent/AU2013256489A1/en not_active Abandoned
- 2013-04-30 CA CA2870505A patent/CA2870505A1/en not_active Abandoned
- 2013-04-30 EP EP13724056.0A patent/EP2845013A2/en not_active Withdrawn
- 2013-04-30 WO PCT/US2013/038880 patent/WO2013166022A2/en active Application Filing
- 2013-04-30 JP JP2015510387A patent/JP6108572B2/en not_active Expired - Fee Related
- 2013-04-30 BR BR112014026936A patent/BR112014026936A2/en not_active IP Right Cessation
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US20090019877A1 (en) | 2006-01-13 | 2009-01-22 | Dale Larson | Systems, Methods and Devices for Frozen Sample Distribution |
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CN104428678A (en) | 2015-03-18 |
BR112014026936A2 (en) | 2017-06-27 |
AU2013256489A1 (en) | 2014-10-30 |
EP2845013A2 (en) | 2015-03-11 |
WO2013166022A3 (en) | 2014-03-13 |
JP6108572B2 (en) | 2017-04-05 |
JP2015516077A (en) | 2015-06-04 |
CA2870505A1 (en) | 2013-11-07 |
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