Laser microdissection system and method for laser microdissection
Patent Information
- Application Number
- CN202411720983.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Priority Date
- 2023-11-30
- Filing Date
- 2024-11-28
- Publication Date
- 2025-05-30
Smart Images
Figure CN120065495A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to a laser microdissection system and a method for laser microdissection. Background Art
[0002] In laser microdissection, a laser is used to cut a sample to remove a small part of the sample, a so-called dissektat. Laser microdissection systems known in the prior art use gravity to collect the dissektat cut from the sample in a collection container arranged below the sample, such as in the wells of a PCR tube or a multi-well plate. Finding the dissektat in the collection container can sometimes be very time-consuming because the dissektat is very small compared to the surface to be searched. In addition, the dissektat may be located not only on the bottom of the collection container but also on the walls of the collection container, so that not only the surface but also the space has to be searched to find the dissektat. Especially in high-throughput experiments using, for example, multi-well plates with 96 or 384 wells, the time loss is particularly disadvantageous. Summary of the Invention
[0003] Therefore, an object of the present invention is to provide a laser microdissection system and a method for laser microdissection that can quickly and simply determine whether the dissektat has been collected in the collection container.
[0004] This object is achieved by a laser microdissection system having the features of claim 1 and by a method having the features of an independent method claim. Advantageous refinements are given in the dependent claims.
[0005] The proposed laser microdissection system includes a microscope stage configured to accommodate a sample to be cut and a collection unit, the collection unit including at least one collection container arranged below the sample. The at least one collection container is arranged and configured to collect the dissektat cut from the sample. The laser microdissection system further includes an optical detection unit and a control unit, the optical detection unit being configured to acquire a content image of the interior of at least one collection container and generate content image data corresponding to the content image. The control unit is configured to process the content image data and determine whether the dissektat is located in at least one collection container based on the content image data and in consideration of previous image data and / or in consideration of reference image data, the previous image data corresponding to a previous image of the interior of at least one collection container taken before cutting the dissektat from the sample, and the reference image data corresponding to a reference image of the interior of a collection container of the same type as at least one collection container.
[0006] The laser microdissection system has a laser light source and is configured to cut off a small part of a sample, i.e., the dissected object, by means of a laser beam generated by the laser light source. The dissected object then falls under the influence of gravity into at least one collection container. In order to be able to determine at this time whether the dissected object has been correctly collected in at least one collection container, at least one collection container is inspected. In the prior art, the inspection of the collection container is carried out manually and visually, that is, manually adjusting the collection container in height and / or laterally and visually searching for the dissected object. In the proposed laser microdissection system, this process is carried out automatically. Thereby, the proposed laser microdissection system can quickly and simply determine whether the dissected object has been collected in at least one collection container. This saves a large amount of time especially in high-throughput experiments.
[0007] In order to inspect at least one collection container, after cutting the dissected object from the sample, the laser microdissection system acquires a content image. Then the laser microdissection system determines based on the content image whether the dissected object is in at least one collection container, that is, whether the dissected object has been correctly collected.
[0008] As another basis for determination, for example, a previous image is used, that is, an image of the interior of at least one collection container that was just taken before cutting the dissected object from the sample. Thus, the laser microdissection system can determine, for example, by comparing the content image with the previous image whether the dissected object has been correctly collected. In addition, a reference image can also be used as one basis or an additional basis for determination. The reference image is an image of the interior of a collection container of the same type as at least one collection container. For example, if at least one collection container is the cap of a PCR tube, the reference image is an image of the cap of another PCR tube having the same dimensions as at least one collection container.
[0009] The sample to be cut can be a tissue section or a similarly thin biological product and is fixed to the sample carrier, for example, by a membrane. The collection container can in particular be a PCR tube, a closed cap of a PCR tube, or a well of a multi-well plate. However, other common laboratory materials, such as petri dishes, can also be used as collection containers.
[0010] In a further embodiment, the control unit is configured to determine the position of the dissected object inside at least one collection container based on the content image data. The position of the dissected object can be used, for example, to acquire a verification image, and it can be checked by means of the verification image whether the dissected object actually exists inside at least one collection container. Thus, it can be ensured that the control unit has correctly determined that the dissected object is located in at least one collection container. This information can also be used to better process the content image data by the control unit to achieve a more reliable determination. The position of the dissected object can also be used to acquire a detailed image of the dissected object at a high magnification.
[0011] In a further embodiment, the control unit is configured to compare the content image data with previous image data and / or reference image data and to determine based on this comparison whether the anatomical object is located in at least one collection container. In this embodiment, the control unit performs, for example, an image comparison between the content image and the previous image and / or the reference image to determine whether the anatomical object has been correctly collected in at least one collection container. Such an image comparison can be carried out in particular by using known image comparison algorithms. By means of the image comparison, the control unit can quickly and particularly simply determine whether the anatomical object is located in at least one collection container.
[0012] In a further embodiment, the control unit is configured to determine whether the anatomical object is located in at least one collection container by using machine learning methods. As machine learning methods, the control unit can use, for example, one or more neural networks, such as convolutional neural networks, autoencoders or generative adversarial networks. In addition, the control unit can also use other methods as machine learning methods, such as decision trees, random forests or k-nearest neighbor methods. Machine learning methods can distinguish features in images with high precision. Machine learning methods are generally able to recognize patterns and details that are difficult for the human eye to distinguish. Thereby, machine learning methods are particularly suitable for recognizing anatomical objects in content images. Therefore, by using machine learning methods, the control unit can particularly reliably determine whether the anatomical object is located in at least one collection container.
[0013] In a further embodiment, the machine learning method is trained at least by using reference image data as training data to determine whether the anatomical object is located in at least one collection container. For example, the machine learning method has been trained to recognize anatomical objects in content images and, for example, to distinguish scratches, dirt or other objects in the interior of the collection container. In particular, the machine learning method is trained to compare the content image data with previous image data and / or reference image data and to determine based on the comparison whether the anatomical object is located in at least one collection container.
[0014] In a further embodiment, the machine learning method is trained to perform image segmentation of the content image to determine whether the anatomical object is located in at least one collection container. During image segmentation, the content image is divided into regions. Each region corresponds to a different part of the content image, such as the anatomical object, the bottom or wall of at least one collection container, a scratch or dirt. Based on the image segmentation, it is possible to particularly reliably determine whether the anatomical object is located in at least one collection container.
[0015] In a further embodiment, the control unit is configured to at least control the optical detection unit to acquire a content image as a volume image and / or an image with an extended depth of field. For example, the control unit can be configured to control the objective lens of the detection unit pointing at the collection container so that the focal position of the detection unit moves along the optical axis. In this way, a plurality of parallel planes within the collection container can be acquired by means of the detection unit to acquire the content image as a volume image and / or an image with an extended depth of field. In order to obtain an image with an extended depth of field (also referred to as extended depth of field or edof image), images with different focal positions are usually combined into a single image with a high depth of field. The advantage compared to a volume image is that an image with an extended depth of field requires less storage space. In this embodiment, the laser microdissection system generates a content image such that the entire interior of at least one collection container is clearly imaged. Thereby, it is also possible to very reliably determine whether the dissection object is located in at least one collection container when the dissection object is, for example, located on the wall of at least one collection container.
[0016] In a further embodiment, the microscope stage is motor-driven and displaceable along the optical axis of the optical detection unit. The control unit can be configured to displace the microscope stage along the optical axis of the optical detection unit to acquire a content image as a volume image and / or an image with an extended depth of field. For example, the microscope stage can be displaced very precisely by means of a piezoelectric motor. In this embodiment, instead of the focal position of the optical detection unit, the collection unit and / or at least one collection container are displaced along the optical axis of the optical detection unit to acquire a plurality of parallel planes within the collection container. This can also achieve the acquisition of the content image as a volume image and / or an image with an extended depth of field with the aforementioned advantages.
[0017] In a further embodiment, the control unit is configured to determine whether the dissection object is located in at least one collection container taking into account the size of the dissection object. The size of the dissection object can be, for example, the length, width, diameter, and / or area of the dissection object and is determined, for example, automatically based on the area of the sample from which the dissection object has been cut. This area is also referred to as the region of interest or ROI. Taking into account the size of the dissection object, it is possible to find the dissection object in the content image significantly more reliably and, for example, distinguish it from scratches or dirt on at least one collection container.
[0018] In a further embodiment, the laser microdissection system includes a user input unit configured to receive user input. The control unit may be configured to determine the size of the dissection object based on the corresponding user input. In this embodiment, the user defines, for example via the user input, the size of the region of the sample from which the dissection object is to be cut. The control unit may determine the size of the dissection object from this information. Alternatively or additionally, the user may also directly input the size of the dissection object. Taking into account the size of the dissection object when determining whether the dissection object is located in at least one collection container has the above advantages.
[0019] In a further embodiment, the control unit is configured to determine the size of the dissection object based on sample image data corresponding to an image of the sample acquired before or after cutting the dissection object from the sample. In this embodiment, the size of the dissection object is determined automatically by the laser microdissection system. For example, the control unit may determine the size of the region of the sample from which the dissection object has been cut based on an image acquired after cutting the dissection object from the sample. The size of this region is equal to the size of the dissection object. In another example, the control unit may be configured to determine the region from which the dissection object is to be cut based on sample image data corresponding to an image of the sample acquired before cutting the dissection object from the sample. For this purpose, the user may in particular determine a specific structure of the sample, such as a specific cell, that is automatically recognized by the control unit in the image of the sample. The size of this region is also equal to the size of the dissection object. Taking into account the size of the dissection object when determining whether the dissection object is located in at least one collection container has the above advantages.
[0020] In a further embodiment, the laser microdissection system includes an illumination unit configured to emit excitation light for exciting fluorophores. The optical detection unit is configured to acquire fluorescence images. In this embodiment, the illumination unit is configured to excite fluorophores, for example arranged in the sample and thus also in the dissection object, to emit fluorescence. For example, the illumination unit includes one or more laser light sources for generating the excitation light. The fluorophores may in particular be pigments deliberately introduced into the sample to stain specific structures of the sample, such as cell nuclei. This enables the stained structures to be distinguished particularly simply in the fluorescence image of the dissection object.
[0021] In a further embodiment, the control unit is configured to control the illumination unit and the optical detection unit to acquire a content image as a fluorescence image. The dissection object can be found particularly simply in the content image based on the fluorescence emitted from the dissection object. Thereby, it can be determined particularly reliably whether the dissection object is located in at least one collection container. The fluorescence acquired in the fluorescence image may in particular also be the actually interfering autofluorescence, such as a polymer film on which the sample and the dissection object are arranged. Thus, in this embodiment, the effect of the actual interference can be used to reliably determine whether the dissection object is located in at least one collection container.
[0022] In a further embodiment, the control unit is configured to control the illumination unit and the optical detection unit, acquire a verification image as a fluorescence image when the control unit determines that the anatomical object is located in at least one collection container, generate verification image data corresponding to the verification image, and confirm that the anatomical object is located in at least one collection container based on the verification image data. In this embodiment, the laser microdissection system first acquires a content image, in particular as a white light image, and determines whether the anatomical object is located in at least one collection container based on the content image. To confirm whether this determination is correct, the laser microdissection system then acquires a verification image as a fluorescence image. Preferably, the control unit first determines the position of the anatomical object in at least one collection container based on the content image data. The laser microdissection system can then take a verification image at the determined position. With the verification image, it can be checked whether the anatomical object is located in at least one collection container as determined. Thus, for example, if a scratch or dirt on at least one collection container is misidentified as an anatomical object, the ambiguity can be resolved. It is also ensured that the control unit works correctly.
[0023] The invention also relates to a method for laser microdissection. In this method, a sample is arranged above at least one collection container of a collection unit. Here, at least one collection container is arranged and configured to collect the anatomical object cut from the sample. A content image of the interior of at least one collection container is acquired and content image data corresponding to the content image is generated. Based on the content image data and by considering previous image data and / or by considering reference image data, it is determined whether the anatomical object is located in at least one collection container, where the previous image data corresponds to a previous image of the interior of at least one collection container taken before cutting the anatomical object from the sample, and the reference image data corresponds to a reference image of the interior of a collection container of the same type as at least one collection container.
[0024] This method has the same advantages as the claimed laser microdissection system. In particular, the method can be extended by the features of the dependent claims of the laser microdissection system. The above-mentioned laser microdissection system can also be extended by the features described herein with respect to the method. Description of the Drawings
[0025] Embodiments of the present invention will be explained in detail below with reference to the drawings. Shown therein are:
[0026] Figure 1 A schematic diagram of a laser microdissection system according to an embodiment is shown;
[0027] Figure 2 A flowchart of a method for laser microdissection is shown; and
[0028] Figure 3 A schematic diagram of a sample carrier with a sample arranged thereon is shown. Detailed Description of the Invention
[0029] Figure 1 FIG. 3 shows a schematic view of a laser microdissection system 100 according to an embodiment.
[0030] The laser microdissection system 100 is configured to cut out small fragments from a microscopic sample 102, for example from a thin tissue or organ section. The sample 102 is connected to a sample carrier 300, in particular via a membrane 304, which can handle particularly thin samples without damaging them. The following describes an exemplary sample carrier 300. The cut-out part is also referred to as dissected object 104 in microdissection. In the illustrated laser microdissection system 100, the dissected object 104 cut out is collected by gravity in a collection container 106, which is arranged in a collection unit 108 below the sample 102. This arrangement is also referred to as a laser capture microdissection (LCM) system. Figure 3 In the illustrated embodiment, the collection unit 108 is, purely by way of example, a multi-well plate having a plurality of wells, each of which forms a collection container 106. Alternatively, the collection container 106 can also be a PCR tube or the cap of a PCR tube, which can be arranged together with a plurality of additional PCR tubes in a frame. The collection unit 108 and / or the individual collection containers 106 can be removed in order to be able to continue processing the dissected object 104 outside the laser microdissection system 100.
[0031] In Figure 1 the illustrated embodiment, the collection unit 108 is arranged on a microscope stage 110 of the laser microdissection system 100. In this embodiment, the microscope stage 110 is movable so that the collection unit 108 and the sample 102 can be positioned relative to the main body of the laser microdissection system 100. In particular, the microscope stage 110 can be moved along the optical axis O of the laser microdissection system 100, i.e., in the z-direction. This is indicated by the double arrow P in
[0032] FIG. 5. Thereby, the collection unit 108 can be moved vertically, for example, to move the focal position FP within the collection container 106. However, the microscope stage 110 can also be immovable in the z-direction. Figure 1 FIG. 5
[0033] By way of pure example, the laser microdissection system 100 includes a turret 112 disposed on an objective lens 114 thereon. The objective lens 114 disposed on the turret 112 can be alternately pivoted into the optical axis O of the laser microdissection system 100. Thereby, the user can separately select a suitable objective lens 114 for different tasks, such as for cutting the sample 102, for observing the sample 102 or the dissected object 104 in the collection container 106, or for inspecting the collection container 106. In the illustrated embodiment, the turret 112 is immovable relative to the housing of the laser microdissection system 100. However, in another embodiment, the turret 112 is also movable along the optical axis O of the laser microdissection system 100, i.e., in the z-direction, such that the focal position FP of the currently selected objective lens 114 can be displaced relative to the sample 102, the dissected object 104, and / or the collection container 106. Instead of the turret 112, the laser microdissection system 100 may also have a single objective lens holder, and the objective lens 114 is replaceably mounted on the objective lens holder. The objective lens holder is particularly movable along the optical axis O of the laser microdissection system 100 to be able to move the focal position FP of the currently used objective lens 114.
[0034] The laser microdissection system 100 further includes a laser light source 116 and a deflection unit 118, and the laser light source and the deflection unit together form a cutting unit 120 of the laser microdissection system 100. The laser light source 116 is configured to generate a laser 122 for cutting the sample 102. The generated laser 122 is deflected into the objective lens 114 currently pivoted into the optical axis O of the laser microdissection system 100 through the deflection unit 118 and a first beam splitter 124 and is directed at the sample 102. The deflection unit 118 is configured to move the target point of the laser 122 on the sample 102 to cut the sample 102. In an alternative embodiment, the laser microdissection system 100 does not include the deflection unit 118, and the microscope stage 110 is movable perpendicular to the optical axis O such that the target point on the sample 102 can be moved by means of the microscope stage 110.
[0035] The illumination unit 126 of the laser microdissection system 100 is configured to generate illumination light 128 to illuminate an object, such as the sample 102, the dissected object 104, and / or the collection container 106. For example, the illumination unit 126 includes an excitation light source, such as another laser light source, to generate excitation light for exciting a fluorophore to emit fluorescence. However, the illumination unit 126 may also include a white light source for illuminating an object with white light for incident light or transmitted light illumination. By way of pure example, the illustrated illumination unit 126 is configured to generate a light beam composed of the illumination light 128 therefrom, and the light beam is deflected into the objective lens 114 currently pivoted into the optical axis O of the laser microdissection system 100 through a second beam splitter 130 and is directed at the object to be illuminated.
[0036] By way of pure example, the optical dissection unit 132 of the laser microdissection system 100 includes an objective lens 114, a first beam splitter 124, a second beam splitter 130, and a detector element 134 that is currently pivoted into the optical axis O of the laser microdissection system 100. Detection light starting from the sample 102 or the dissected object 104, such as reflected illumination light 128 or fluorescence starting from the sample 102 or the dissected object 104, is deflected towards the detector element 134 by the first beam splitter 124 and the second beam splitter 130. The detector element 134 collects the detection light to generate an image of the sample 102 or the dissected object 104. The detector element 134 also generates image data corresponding to the image. The optical detection unit 132 can be configured in particular to collect fluorescence images.
[0037] The laser microdissection system 100 further includes a control unit 136 that is connected to the microscope stage 110, the turret 112, the cutting unit 120, the illumination unit 126, and the optical detection unit 132 and is configured to control the aforementioned elements. The control unit 136 exemplarily includes a user input unit 138 that is configured to receive a user input from the user. In addition, the control unit 136 is configured to control the laser microdissection system 100 to perform a laser microdissection method. The following refers to Figure 2 Describe this method.
[0038] Figure 2 A flowchart of a method for laser microdissection is shown.
[0039] This method can be performed in particular by the laser microdissection system 100 described according to Figure 1 In this method, the dissected object 104 is cut from the sample 102 and collected by the collection unit 108. It is further determined whether the dissected object 104 is correctly collected in the collection container 106. The method starts in step S200.
[0040] In an optional step S202, the collection unit 108 is placed in the laser microdissection system 100 and arranged on the microscope stage 110. This can be done manually by the user or by a robotic arm that is configured to manipulate the collection unit 108. The robotic arm can be controlled by the control unit 136. The collection unit 108 can also be part of the microscope stage 110. In this embodiment of the laser microdissection system 100, the respective collection containers 106 can be arranged in the collection unit 108 in step S202, for example, manually by the user or automatically by the robotic arm. In an alternative embodiment of the method, the collection unit 108 and the collection container 106 are already arranged when the method starts in step S200.
[0041] In the also optional step S204, the control unit 136 controls the optical detection unit 132 to acquire a previous image of the interior of the collection container 106 of one of the anatomical specimens 104 to be collected by the collection unit 108. The optical detection unit 132 generates previous image data corresponding to the previous image. This previous image data can be used in a further course of the method to perform an image comparison and thus determine whether the anatomical specimen 104 is correctly collected in the collection container 106.
[0042] In step S206, the sample 102 is arranged above the collection container 106 such that the anatomical specimen 104 cut from the sample 102 can be collected in the collection container 106. In particular, the sample 102 can be arranged manually by the user. Alternatively, the sample 102 can also be arranged above at least one collection container 106 by a robotic arm. In the optional step S208, the control unit 136 controls the optical detection unit 132 to acquire a first image of the sample 102. The detection unit 132 generates first sample image data corresponding to the first image of the sample 102. In a subsequent step S210, for example, the user can select a ROI to be cut by the laser microdissection system 100 based on the first image of the sample 102. The following describes an exemplary first image of the sample 102. Figure 3 Describe an exemplary first image of the sample 102.
[0043] In step S210, the area of the sample 102 to be cut off is selected. This can be done fully automatically by the control unit 136 based on the first sample image data. For example, the control unit 136 determines the position of a specific structure of the sample 102, such as a specific type of cell, based on the first sample image data. Alternatively, the area of the sample 102 to be cut off can be determined by the user, in particular by user input. Then, in a subsequent step S212, the control unit 136 controls the cutting unit 120 to cut off the area to be cut off to produce the anatomical specimen 104.
[0044] In the optional step S214, the control unit 136 controls the optical detection unit 132 to acquire a second image of the sample 102. The detection unit 132 generates second sample image data corresponding to the second image of the sample 102. Based on the second sample image data, the control unit 136 can derive, in particular, the dimensions of the anatomical specimen 104, such as the length, width, diameter and / or area of the anatomical specimen 104, where the dimensions of the anatomical specimen 104 are equivalent to the corresponding dimensions of the cut-off area. The dimensions of the anatomical specimen 104 can also be determined according to the corresponding dimensions of the ROI, for example based on the first image data. In addition, the user can also input the dimensions of the anatomical specimen 104 as user input.
[0045] In step S216, the control unit 136 controls the optical detection unit 132 to acquire a content image of the interior of the collection container 106. The optical detection unit 132 generates content image data corresponding to the content image. The content image can be acquired as a fluorescence image. Thus, it is possible to particularly simply distinguish the anatomical object 104 by fluorescence starting from the anatomical object 104, the fluorescence starting, for example, from a fluorophore introduced into the sample 102 or generated by autofluorescence. In particular, the diaphragm 304 on which the sample 102 is applied may have autofluorescence. In particular, the control unit 136 controls the optical detection unit 132 to acquire the content image such that the content image is acquired as a volume image or an image with an extended depth of field. In both cases, the content image corresponds to an extended volume within the interior of the collection container 106. Thus, it is also possible to determine whether the anatomical object 104 is attached to the wall portion of the collection container 106. To be able to acquire a volume image or an image with an extended depth of field, the control unit 136 may in particular control the microscope stage 110 to move in the z-direction.
[0046] Then, in step S218, the control unit 136 determines whether the anatomical object 104 is in the collection container 106 based on the content image data. For example, if the size of the anatomical object 104 is determined in step S216, the control unit 136 may take this size into account when making the determination. In a first exemplary method, the control unit 136 compares the content image with a previous image acquired in step S204 to determine whether the anatomical object 104 has been collected in the collection container 106. Instead of or in addition to the previous image, the control unit 136 may also compare the content image with at least one reference image, which is an image of the interior of a collection container 106 of the same type as the collection container 106 in which the anatomical object 104 is to be collected. For example, an image of a well of a microplate, the well having the same size as the well for collecting the anatomical object 104. To compare the images, the control unit 136 processes the content image data and the previous image data and / or the reference image data, which corresponds to the reference image, using an image comparison method, in particular a machine learning method. In another exemplary method, the control unit 136 uses a machine learning method that is trained at least based on the reference image data to determine whether the anatomical object 104 has been collected in the collection container 106. For example, the machine learning method may be an image segmentation method, in particular a method for semantic segmentation, which segments the content image to distinguish the anatomical object 104.
[0047] In optional step S220, control unit 136 determines the position of the anatomical object 104 in collection container 106 based on the content image data. This enables the anatomical object 104 to be located in collection container 106, for example, in order to acquire a detailed mapping of the anatomical object 104. In a further optional step S222, control unit 136 controls optical detection unit 132 to acquire a verification image of the interior of collection container 106. Optical detection unit 132 generates verification image data corresponding to the verification image. In particular, the verification image is a detailed mapping of the anatomical object 104 at the position determined in step S220 within the interior of collection container 106. Alternatively or additionally, the verification image can be a fluorescence image, such that the anatomical object 104 can be distinguished based on fluorescence. Whether the anatomical object 104 has been collected correctly can be confirmed based on the verification image.
[0048] The method ends in step S224.
[0049] Figure 3 A sample carrier 300 on which a sample 102 is arranged is shown schematically.
[0050] Figure 3 Sample carrier 300 shown therein has, purely by way of example, the dimensions of a glass slide as are common in a microscope. Thereby, sample carrier 300 is compatible with other laboratory instruments, such as a microscope or a slide scanner. Sample carrier 300 has a frame 302 including a recess, via which a diaphragm 304 is tensioned, on which sample 102 is applied and the diaphragm can be cut by laser 122. Diaphragm 304 is made, for example, of polyethylene naphthalate which fluoresces in visible light. As an alternative variant of the sample carrier (not shown here), a glass slide without an opening can also be used, on which a laser-cuttable film is tensioned and which is fixed only in the edge region of the glass slide, for example by bonding.
[0051] Figure 3 It also has a section 306 shown by a dashed box, which section corresponds to a previous image. ROI 308, i.e., the region of sample 102 that is to be cut off to obtain the anatomical object 102, is located within this section 306. Purely by way of example, ROI 308 is circular and is shown by a dashed circle.
[0052] The term “and / or” includes all combinations of one or more of the listed elements belonging thereto and can be abbreviated with “ / ”.
[0053] Although several scenarios are described within the scope of the device, it should be clear that these scenarios are also a description of the corresponding method, where a box or a device corresponds to a method step or a function of a method step. Similarly, the scenarios described in the method steps are also a description of the corresponding box or element or characteristic of the corresponding device.
[0054] Reference numerals list
[0055] 100 Laser Microdissection System
[0056] 102 samples
[0057] 104 Anatomy
[0058] 106 Collection Container
[0059] 108 Collection Unit
[0060] 110 microscope stage
[0061] 112 lens changer
[0062] 114 objective lens
[0063] 116 Laser light source
[0064] 118 deflection unit
[0065] 120 cutting unit
[0066] 122 Laser
[0067] 124 Beam Splitter
[0068] 126 Lighting Units
[0069] 128 illumination light
[0070] 130 Beam Splitter
[0071] 132 Detection Unit
[0072] 134 Detection element
[0073] 136 Control Unit
[0074] 138 User input unit
[0075] 300 sample carriers
[0076] 302 Framework
[0077] 304 Diaphragm
[0078] 306 Part
[0079] 308 Region of Interest ROI
Claims
1. A laser microdissection system (100), comprising: a microscope stage (110) configured to accommodate a sample (102) to be cut and a collecting unit (108), the collecting unit comprising at least one collecting container (106) arranged below the sample (102), wherein the at least one collecting container (106) is arranged and configured to collect anatomical matter (104) cut from the sample (102); an optical detection unit (132) configured to capture a content image of the interior of the at least one collection container (106) and generate content image data corresponding to the content image; and A control unit (136) configured to process the content image data and to determine whether the anatomical object (104) is located in the at least one collecting container (106) based on the content image data and taking into account previous image data and / or taking into account reference image data, wherein the previous image data corresponds to a previous image of the interior of the at least one collecting container (106) taken before the anatomical object (104) is cut from the sample (102), and the reference image data corresponds to a reference image of the interior of a collecting container (106) of the same type as the at least one collecting container (106).
2. The laser microdissection system (100) according to claim 1, wherein: The control unit (136) is configured to determine a position of the anatomical object (104) within the interior of the at least one collection container (106) based on the content image data.
3. The laser microdissection system (100) according to claim 1 or 2, wherein: The control unit (136) is configured to compare the content image data with the previous image data and / or the reference image data and determine whether the anatomy (104) is located in the at least one collection container (106) based on the comparison.
4. The laser microdissection system (100) according to any one of the preceding claims, wherein: The control unit (136) is configured to determine whether the anatomical object (104) is located in the at least one collection container (106) by using a machine learning method.
5. The laser microdissection system (100) according to claim 4, wherein: The machine learning method is trained by using at least the reference image data as training data to determine whether the anatomy (104) is located in the at least one collection container (106).
6. The laser microdissection system (100) according to claim 4 or 5, wherein: The machine learning method is trained to perform image segmentation of the content image to determine whether the anatomy (104) is located in the at least one collection container (106).
7. The laser microdissection system (100) according to any one of the preceding claims, wherein: The control unit (136) is configured to control at least the optical detection unit (132) to acquire a content image as a volume image and / or an image with an extended depth of field.
8. The laser microdissection system (100) according to claim 7, wherein: The microscope stage (110) is motor-driven and displaceable along the optical axis of the optical detection unit (132), and wherein the control unit (136) is configured to displace the microscope stage (110) along the optical axis of the optical detection unit (132) to acquire a content image as a volume image and / or an image with an extended depth of field.
9. The laser microdissection system (100) according to any one of the preceding claims, wherein: The control unit (136) is configured to determine whether the anatomical object (104) is located in the at least one collection container (106) taking into account the size of the anatomical object (104).
10. The laser microdissection system (100) according to claim 9, wherein: The laser microdissection system includes a user input unit (138) configured to receive user input, wherein the control unit (136) is configured to determine a size of the anatomical object (104) based on the corresponding user input.
11. The laser microdissection system (100) according to claim 9 or 10, wherein: The control unit (136) is configured to determine a size of the anatomical object (104) based on sample image data corresponding to an image of the sample (102) acquired before or after the anatomical object (104) is cut from the sample (102).
12. The laser microdissection system (100) according to any one of the preceding claims, wherein: The laser microdissection system comprises an illumination unit (126) configured to emit excitation light for exciting fluorophores, wherein the optical detection unit (132) is configured to acquire a fluorescence image.
13. The laser microdissection system (100) according to claim 12, wherein: The control unit (136) is configured to control the illumination unit (126) and the optical detection unit (132) to acquire a content image as a fluorescent image.
14. The laser microdissection system (100) according to claim 12 or 13, wherein: The control unit (136) is configured to control the lighting unit (126) and the optical detection unit (132), to acquire a verification image as a fluorescent image when the control unit (136) determines that the anatomical object (104) is located in the at least one collection container (106), to generate verification image data corresponding to the verification image, and to confirm that the anatomical object (104) is located in the at least one collection container (106) based on the verification image data.
15. A method for laser microdissection, wherein: a) placing a sample (102) on at least one collecting container (106) of a collecting unit (108), wherein: The at least one collection container (106) is arranged and configured to collect dissection (104) excised from the sample (102); b) collecting a content image of the interior of the at least one collection container (106) and generating content image data corresponding to the content image, and c) determining whether the anatomical object (104) is located in the at least one collecting container (106) based on the content image data and by considering previous image data and / or by considering reference image data, wherein the previous image data corresponds to a previous image of the interior of the at least one collecting container (106) taken before the anatomical object (102) is cut from the sample (102), and the reference image data corresponds to a reference image of the interior of a collecting container (106) of the same type as the at least one collecting container (106).