Optical imaging sensor alignment for an epifluorescence microscope

Abstract

A method for aligning an optical imaging sensor for an epifluorescence microscope is provided. The method includes receiving an image of a target pattern of an alignment target positioned near a microscope objective lens. The method further includes determining an image quality for each element of the target pattern and generating a heatmap for the image based on the determined image quality for each element of the target pattern. The heatmap indicates focusing quality and variation over a field-of-view of the objective lens. The method further includes determining focusing metrics based on fitting the heatmap to a distribution profile, and providing the focusing metrics to a user, where the focusing metrics are used to adjust alignment of the optical imaging sensor to improve image quality.

Description

Docket No. TP388527WO1 OPTICAL IMAGING SENSOR ALIGNMENT FOR AN EPIFLUORESCENCE MICROSCOPE CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of priority of U.S. Provisional Application No. 63 / 689,369, filed on August 30, 2024, which is incorporated herein by reference. BACKGROUND

[0002] Optical systems have been used to monitor, measure, and / or analyze biological and biochemical reactions when performing biological analyses. Such systems are commonly used in sequencing, genotyping, polymerase chain reactions (PCR), and other biochemical reactions to monitor progress or analyze samples after reactions are complete, providing quantitative data.

[0003] For example, an optical system may be used in DNA-DNA hybridization arrays to illuminate fluorescent DNA-binding dyes or fluorescent probes to produce fluorescent signals indicative of the degree of similarity between sample and probe. In a hybridization analysis, arrays are set up with selected sets of DNA sequences of interest. If a sample has complementary sequences to the target DNA in the array, a fluorescent dye can be attached. When excitation light shines on the DNA array after hybridization, array spots fluoresce if a dye is attached. An optical system is needed to measure the fluorescent emission light. In these optical systems, fluorescent emission data is measured by taking multiple images at each sub- array location to scan an entire sample holder. Accurate results require excellent image quality, and this in turn requires a high degree of alignment of the optical imaging sensor with respect to the epifluorescence microscope optics.

[0004] Achieving a high degree of alignment is especially difficult where applications require a custom-build microscope system. Such custom systems typically feature a mixture of standardized and non-standardized components and do not follow established microscope system design guidelines. The standard alignment tools and methods are often not well adapted and thus not effective in producing the needed alignment. When coupled with sensitive mechanical tolerances, custom systems can feature significant residual optical imaging sensor misalignment which significantly degrades image quality.Docket No. TP388527WO1

[0005] These standard alignment tools and methods for microscopes also fail to meet the requirements for large, fine-pitched sample arrays. The tools include USAF1951 targets, ISO standard charts, and their variants, to measure and optimize image quality. Optical resolution is calculated using the contrast from bar patterns, or MTF (Modulation Transfer Function) from slanted edge targets. These fail to meet alignment requirements for three reasons. First, they are insensitive to image decentration and tilt. Second, they typically feature a small number of elements, sampling only a small number of locations across the field of view, and the target elements only cover only a modest portion of the field of view required (for example, two-thirds) whereas the sample array features to be measured are small, densely packed, and cover the entire field of view. Third, they often require mathematical processing and do not provide real-time feedback to guide the user to quickly and effectively adjust the alignment. Methods to overcome this have typically involved tedious, time-consuming iteration, with low effectiveness.

[0006] Moreover, end-users are requiring the ability to measure greater numbers of reactions per test or experiment, including simultaneous measurements of arrays with features that are even smaller, more densely-packed, and extending to the very edge of the field of view, with a very high degree of uniformity across the field of view. This requires even more effective alignment to provide the high image quality that assures accuracy and sensitivity.

[0007] Thus, the combination of having large numbers of array samples uniformly over a large field of view and the desire to perform experiments in a faster and reliable manner has created a need for optical systems that scan accurately and provide high optical performance for observing, testing, and / or analyzing one or more biological samples. SUMMARY

[0008] In one exemplary embodiment, a method for aligning an optical imaging sensor for a fluorescence microscope is provided. The method includes receiving an image of a target pattern of an alignment target positioned near a microscope objective lens. The method further includes determining an image quality for each element of the target pattern and generating a heatmap for the image based on the determined image quality for each element of the target pattern. The heatmap indicates focusing quality and variation over a field-of-view of the objective lens. The method further includes determining focusing metrics based on fitting the heatmap to aDocket No. TP388527WO1 distribution profile, and providing the focusing metrics to a user, where the focusing metrics are used to adjust alignment of the optical imaging sensor to improve image quality.

[0009] In another exemplary embodiment, a system for aligning an optical imaging sensor is provided. The system includes an alignment target positioned near a microscope objective lens, where the alignment target includes a target pattern. The system also includes a processor configured to: receive an image of the target pattern, determine an image quality for each element of the target pattern, generate a heatmap for the image based on the determined image quality for each element of the target pattern, where the heatmap indicates focusing quality and variation over a field-of-view of the objective lens, determine focusing metrics based on fitting the heatmap to a distribution profile, and provide the focusing metrics to a user, where the focusing metrics are used to adjust alignment of the optical imaging sensor to improve image quality. The system further includes an optical imaging sensor fixture configured to adjust the position of the optical imaging sensor based on the focusing metrics. DESCRIPTION OF THE FIGURES

[0010] FIG. 1 illustrates a block diagram of a genotyping instrument upon which embodiments of the present teachings may be implemented.

[0011] FIG. 2 illustrates an exemplary optical imaging sensor calibration system according to various embodiments described herein.

[0012] FIG. 3 illustrates a flowchart of a method for calibrating a camera alignment according to various embodiments described herein.

[0013] FIG. 4 illustrates an exemplary computing system for implementing various embodiments described herein.

[0014] FIG. 5 illustrates an exemplary distributed network system according to various embodiments described herein.

[0015] FIG. 6 illustrates a diagram of an inverted fluorescent optical system according to various embodiments described herein.Docket No. TP388527WO1

[0016] FIG. 7 illustrates a camera alignment fixture according to various embodiments described herein.

[0017] FIG. 8A and FIG. 8B illustrate perspective views of an exemplary camera mount according to various embodiments described herein.

[0018] FIG. 9 illustrates a perspective view of another exemplary camera mount according to various embodiments described herein.

[0019] FIG. 10A and FIG. 10B illustrate exemplary perspective views of an alignment target moveable stage according to various embodiments described herein.

[0020] FIG. 11 illustrates an exemplary alignment target according to various embodiments described herein.

[0021] FIG. 12 illustrates an exemplary method for generating focusing metrics according to various embodiments described herein.

[0022] FIGS. 13A-13B depict an optical imaging sensor and an image plane according to various embodiments described herein.

[0023] FIGS. 14A-14C illustrate examples of tilt angles between an image plane and optical imaging sensor according to various embodiments described herein.

[0024] FIG. 15A and FIG. 15B illustrate determining a tilt metric according to various embodiments described herein.

[0025] FIG. 16 illustrates a flowchart of a method of calibrating optical imaging sensor alignment according to various embodiments described herein. DETAILED DESCRIPTION

[0026] To provide a more thorough understanding of the present invention, the following description sets forth numerous specific details, such as specific configurations, parameters, examples, and the like. It should be recognized, however, that such description is not intended asDocket No. TP388527WO1 a limitation on the scope of the present invention but is intended to provide a better description of the exemplary embodiments.

[0027] In various embodiments, the devices, instruments, systems, and methods described herein may be used to detect one or more types of biological components of interest. These biological components of interest may be any suitable biological target including, but are not limited to, DNA sequences (including cell-free DNA), RNA sequences, genes, oligonucleotides, molecules, proteins, biomarkers, cells (e.g., circulating tumor cells), or any other suitable target biomolecule.

[0028] Embodiments of the present disclosure are generally directed to devices, instruments, systems, and methods for monitoring or measuring a biological reaction for a large number of small volume samples. As used herein, samples may be referred to as sample volumes, or reactions volumes, for example.

[0029] Hybridization of the fluorescent dye to the specimen results in fluorescent emission light. Hybridization analyses are an inexpensive way to screen a large number of targets. As such, this method is a simple and useful in a way to screen for hereditary susceptibility to different problems, such as cancer, sickle cell disease, Alzheimer’s, thyroid disease, hereditary deafness or blindness, for example. It can also be used to promote health and productivity in agriculture by using it on animals and plants as part of good breeding (e.g. corn with high yield that is not susceptible to blight or mold).

[0030] In a hybridization analysis, there are millions of array spots featuring short strands of DNA on fused silica substrates. Arrays are set up with selected sets of DNA sequences of interest. A fluid sample is prepared for a particular person, plant, or animal’s DNA. The array is then immersed in this sample and baked in a hybridization oven, where, if the subject’s DNA is complementary to the DNA targets on the array, they will bond (hybridize). When they hybridize, a ligation region is formed near the bond of the array DNA and the sample DNA. Thus, a fluorescent dye can be attached to this ligation region. When excitation light shines on the DNA array after hybridization, array spots light up (fluoresce) if dye is attached. This means that location (with its known DNA array content) was complementary with the sample’s DNA.Docket No. TP388527WO1 Genotyping Instrument

[0031] FIG. 1 illustrates a block diagram of a genotyping instrument upon which embodiments of the present teachings may be implemented.

[0032] In various embodiments, nucleic acid sequence data can be generated using various techniques, platforms or technologies, including, but not limited to: hybridization-based systems, capillary electrophoresis, microarrays, ligation-based systems, polymerase-based systems, direct or indirect nucleotide identification systems, pyrosequencing, ion- or pH-based detection systems, electronic signature-based systems, fluorescent-based detection systems, single molecule methods, etc.

[0033] Various embodiments of genotyping platforms, such as a nucleic acid sequencer, can include components as displayed in the block diagram of FIG. 1. Various embodiments of biological analysis instrument 100 can provide for automated sequencing that can be used to gather sequence information from a plurality of sequences in parallel, such as substantially simultaneously. In various embodiments, biological analysis instrument 100 can determine the sequence of a nucleic acid, such as a polynucleotide or an oligonucleotide. The nucleic acid can include DNA or RNA, and can be single stranded, such as ssDNA and RNA, or double stranded, such as dsDNA or a RNA / cDNA pair. In various embodiments, the nucleic acid can include or be derived from a fragment library, a mate pair library, a ChIP fragment, or the like. In particular embodiments, biological analysis instrument 100 can obtain the sequence information from a single nucleic acid molecule or from a group of substantially identical nucleic acid molecules.

[0034] According to various embodiments, biological analysis instrument 100 can include a control system 102. Control system 102 controls fluidic delivery from fluidic systems 108 to samples 104. Fluidic systems 108 may include a reagent reservoir for storing reagents. The reagents can include RNA-based primers, forward / reverse DNA primers, oligonucleotide mixtures for ligation sequencing, nucleotide mixtures for sequencing-by-synthesis, optional ECC oligonucleotide mixtures, buffers, wash reagents, blocking reagent, stripping reagents, and the like. Fluidic systems 108 are used for hybridization and wash sequences. Further, heating andDocket No. TP388527WO1 cooling elements 106 are used in the hybridization step of samples 104 according to various embodiments.

[0035] In various embodiments, samples 104 may be in reactions sites within a sample holder. A sample holder may be, according to various embodiments described herein, an array plate, a microarray, a flow cell, a substrate, a multi-well tray, such as a standard microtiter 96- well, a 384-well plate, a 24-well plate, or a microcard, or a substantially planar support, such as a glass or plastic slide or a silicon chip, or the like. Further, according to various embodiments described herein, reaction sites may include, but are not limited to, wells, through-holes, indentations, spots, cavities, sample retainment regions, and reaction chambers, for example. Samples 104 may be included in multiple lanes, multiple channels, multiple wells, or other means of processing multiple sample sets substantially simultaneously.

[0036] Optical system 110 scans each reaction site to generate an image that is analyzed for fluorescence. Optical system 110 includes an optical sensor, such as an imaging or detection sensor. For example, the optical imaging or detection sensor can include a CCD, a CMOS, an ion sensor, such as an ion sensitive layer overlying a CMOS, a current detector, or the like. Optical system 110 is further described below with reference to FIG. 6.

[0037] Furthermore, an optical microscope is a type of microscope that uses visible light and a series of lenses to magnify images of small objects.

[0038] The key components of an optical microscope include: a light source, a system of lenses or mirrors for directing the light from the light source to the specimen, one or more objective lenses (if more than one, then they are located on a rotatable turret so that only one is selected at any time), an eyepiece or tube lens, and an optical imaging sensor (the eye or a camera). Magnification is achieved by a combination of the objective and eyepiece or tube lens.

[0039] In various embodiments described herein, an epifluorescent microscope is used. Fluorescence is used to perform biological analyses. One range of wavelengths is incident on the sample, which fluoresces, converting a portion of that incident light into a second range of wavelengths (which is longer in wavelength). “Epi” means we are shining the excitation light onto the sample from the same of the sample from which we collect the emission light.Docket No. TP388527WO1

[0040] This is enabled by a dichroic filter cube consisting of an excitation bandpass filter, a dichroic filter (reflecting the excitation light and transmitting the longer wavelength emission light), and an emission bandpass filter (which eliminates all excitation wavelengths so that the output of the microscope is only emission light).

[0041] According to various embodiments, control system 102 controls various elements of biological analysis instrument 100. For example, control system 102 controls heat / cool elements 106 in conjunction with fluidic systems 108 to perform some processing steps of the biological analysis. Further, control system 102 controls optical system 110. Control system 102 may be accessible to an end user through user interface 112 of biological analysis instrument 100. According to various embodiments, control system 102 includes a computer system, as depicted in FIG. 4, which provides the control the function biological analysis instrument 100, as well as the user interface 112. Control system 102 may provide data processing, display and report preparation functions. All such instrument control functions may be dedicated locally to the biological analysis instrument 100, or control system 102 may be part of a more remote distributed system as depicted in FIG. 5 in various embodiments.

[0042] As mentioned above, user interface 112 may provide user access to control system 102. Further, user interface 112 displays data collected in useful and in an easily to digest manner according to embodiments of the present teachings. User interface 112 may be local to biological analysis instrument 100 in some embodiments. In other embodiments, user interface 112 may be remote to biological analysis instrument100 and be connected to a distributed network. Optical Imaging Sensor Alignment System

[0043] As discussed above, in performing biological analyses, a large number of samples is tested and analyzed. Quickly performing the biological analysis has been previously hindered by a lengthy and difficult processes to align the optical imaging sensor and microscope of a biological analysis instrument.

[0044] According to various embodiments described herein, systems and methods for achieving real-time feedback for angular and linear position of an optical imaging sensor andDocket No. TP388527WO1 improving focusing quality across the field-of-view with high spatial resolution is provided. Further, an alignment process that is simple and deterministic that is quick to provide high quality images is provided according to various embodiments described herein.

[0045] The present teachings relate to precision optical alignment for high-quality and uniform microscopy imaging. More particularly, embodiments of the present invention relate to apparatus and method for aligning a microscopy system to compensate for image tilt and decentration from optics and to achieve high resolution and uniform image quality over the field of view.

[0046] FIG. 2 illustrates an exemplary optical imaging sensor alignment system according to various embodiments described herein. The optical imaging sensor alignment system includes a microscope 210, an optical imaging sensor alignment fixture 218, an alignment target fixture 206, an autocollimator 202, an illumination light source 204, a computing system 222 with alignment software 234 and a user interface 226. Microscope 210 includes microscope body 212, objective lens 208, imaging tube lens 214, optical imaging sensor mount 216, and optical imaging sensor 220.

[0047] The positions of objective lens 208 and imaging tube lens 214 are fixed and aligned based on the mechanical design and machining tolerances of microscope body 212.

[0048] Optical imaging sensor mount 216 can be unlocked to provide an adequate amount of linear and angular movement range to optical imaging sensor 220, while keeping optical imaging sensor 220 connected to microscope 210. Optical imaging sensor mount 216 can also be locked so it secures optical imaging sensor 220 to microscope body 212 tightly. Examples of an optical imaging sensor mount are shown in FIGS. 8A, 8B, and 9.

[0049] Optical imaging sensor alignment fixture 218 also holds optical imaging sensor 220 while providing independent adjustment in 6 degrees of freedom to change the linear and angular position of optical imaging sensor 220 to an optimal position based on alignment calibration according to various embodiments described herein. Optical imaging sensor alignment fixture 218 may be removed when optical imaging sensor 220 is fixed in an optimal position based on various embodiments.Docket No. TP388527WO1

[0050] Alignment target fixture 206 includes a target holder, a custom alignment target 228, and a piezo stage. Alignment target 228 is fixed to the piezo stage and its position can be changed in sub-micrometer step size closer and away from objective lens 208, defined as the z axis. The target holder has an adjustment mechanism to angularly adjust the piezo stage. Alignment target 228 has micro-level pattern array over the entire field of view of the microscope system.

[0051] Autocollimator 202 is a precision angular measurement instrument and is used for optical imaging sensor 220 and alignment target 228. Illumination light source 204 lights alignment target 228 in the wavelength of interest.

[0052] Further, computer 222 connects to optical imaging sensor 220, illumination light source 204, and the piezo motor for device control and data acquisition.

[0053] FIG. 3 illustrates a flowchart of method 300 for calibrating an optical imaging sensor alignment utilizing system 200 according to various embodiments described herein.

[0054] In step 302, an image of alignment target 228 positioned near a microscope objective lens is received. Alignment software 224 controls optical imaging sensor 220 to capture the image.

[0055] In step 304, an image quality for each element of the target pattern of alignment target 228 is determined. Alignment software 224 acquires image of alignment target 228 from optical imaging sensor 220, processes the image of the micro-level pattern array, and analyzes the image quality of each element of the micro-level patterns at individual field of view position.

[0056] In step 306, a real-time heatmap for the image based on the determined image quality for each element of the target pattern is generated. The heatmap indicates focusing quality and variation over an entire field-of-view of the objective lens.

[0057] For example, in one embodiment, alignment target 228 has a pinhole array target pattern where each individual pinhole has a diameter of a few micrometers. All pinholes may be identical in shape and size. The pinholes of the target pattern may be spaced based on the pinhole size is some examples. Alignment software 224 identifies individual pinholes in anDocket No. TP388527WO1 image and analyzes its image quality using a Fourier Transfer algorithm. The alignment software divides the field of view into multiple bins. The analysis results of the pinholes within a bin are average or summarized to a single value as the average performance of the bin. The alignment software visualizes the values of the bins as a heatmap.

[0058] In step 308, focusing metrics based on fitting the heatmap to a distribution profile are determined. Then, in step 310, the focusing metrics are provided to a user. The focusing metrics are used to adjust alignment of the optical imaging sensor to improve image quality.

[0059] The Fourier Transform process to generate a heatmap is further described in an example below.

[0060] Alignment software 224 further fits the heatmap into a 2-dimentional Gaussian formula and uses the critical parameters of the fitted 2D Gaussian as the focusing metrics of the microscope system. Alignment software 224 processes real-time image sequences in high speed so that any change to the microscope system alignment will generate real-time feedback. Real- time feedback may be provided to a user on user interface 226. A user may also use alignment software 224 to control the piezo stage of alignment target fixture 206 to set the position of alignment target 228.

[0061] Alignment software 224 further controls the piezo motor to move alignment target 228 and acquires a stack of through focus images along the z-axis, or z-stack images, of alignment target 228. In some embodiments, a step may be a micrometer or a sub-micrometer. The heatmaps for the z-stack images are generated and compared to calculate the best focus position for different field positions. Image tilt can further be calculated from the analysis of the z-stack images. Based on the analysis of individual images and the stack of images, alignment software 224 guides the user to align optical imaging sensor 220 to be in the best position.

[0062] In various embodiments, the method also includes adjusting tilt angles of the imaging sensor 220. For each tilt angle of the imaging sensor 220, alignment target 228 may be moved in steps to generating z-stack images. In various embodiments, the z-stack images are included in a z-sweep image set for analysis. Alignment software 224 calculates the image tilt based on the z- sweep images. Alignment software 224 may further compare the image tilt of different tilt anglesDocket No. TP388527WO1 of the image sensor 220 and provide the estimated best angular position of the optical imaging sensor to minimize image tilt. A determination of image tilt is described further below with reference to FIGS. 13A-B, 14A-C, and 15A-B.

[0063] According to various embodiments described herein, real-time feedback of focusing quality across the entire field of view with high spatial resolution down to micrometers and high sensitivity to optical imaging sensor angular position change is provided. Various embodiments of the present teachings benefit microscope use for biological analysis instruments greatly by simplifying the alignment procedure using automated motion control and image processing and user guided software.

[0064] Computing System

[0065] FIG. 4 illustrates an exemplary computing system for implementing various embodiments described herein.

[0066] Additionally, the described implementation includes software, but the present teachings may be implemented as a combination of hardware and software or in hardware alone. The present teachings may be implemented with both object-oriented and non-object-oriented programming systems.

[0067] FIG. 4 is a block diagram that illustrates a computer system 400 that may be employed to carry out processing functionality, according to various embodiments. Instruments to perform experiments may be connected to the exemplary computing system 400. Computing system 400 can include one or more processors, such as a processor 404. Processor 404 can be implemented using a general or special purpose processing engine such as, for example, a microprocessor, controller or other control logic. In this example, processor 404 is connected to a bus 402 or other communication medium.

[0068] Further, it should be appreciated that computing system 400 of FIG. 4 may be embodied in any of a number of forms, such as a rack-mounted computer, mainframe, supercomputer, server, client, a desktop computer, a laptop computer, a tablet computer, hand- held computing device (e.g., PDA, cell phone, smart phone, palmtop, etc.), cluster grid, netbook, embedded systems, or any other type of special or general purpose computing device as may beDocket No. TP388527WO1 desirable or appropriate for a given application or environment. Additionally, computing system 400 can include a conventional network system including a client / server environment and one or more database servers, or integration with LIS / LIMS infrastructure. A number of conventional network systems, including a local area network (LAN) or a wide area network (WAN), and including wireless and / or wired components, are known in the art. Additionally, client / server environments, database servers, and networks are well documented in the art. According to various embodiments described herein, computing system 400 may be configured to connect to one or more servers in a distributed network. Computing system 400 may receive information or updates from the distributed network. Computing system 400 may also transmit information to be stored within the distributed network that may be accessed by other clients connected to the distributed network.

[0069] Computing system 400 may include bus 402 or other communication mechanism for communicating information, and processor 404 coupled with bus 402 for processing information.

[0070] Computing system 400 also includes a memory 406, which can be a random-access memory (RAM) or other dynamic memory, coupled to bus 402 for storing instructions to be executed by processor 404. Memory 406 also may be used for storing temporary variables or other intermediate information during execution of instructions to be executed by processor 404. Computing system 400 further includes a read only memory (ROM) 408 or other static storage device coupled to bus 402 for storing static information and instructions for processor 404.

[0071] Computing system 400 may also include a storage device 410, such as a magnetic disk, optical disk, or solid-state drive (SSD) is provided and coupled to bus 402 for storing information and instructions. Storage device 410 may include a media drive and a removable storage interface. A media drive may include a drive or other mechanism to support fixed or removable storage media, such as a hard disk drive, a floppy disk drive, a magnetic tape drive, an optical disk drive, a CD or DVD drive (R or RW), flash drive, or other removable or fixed media drive. As these examples illustrate, the storage media may include a computer-readable storage medium having stored therein particular computer software, instructions, or data.

[0072] In alternative embodiments, storage device 410 may include other similar instrumentalities for allowing computer programs or other instructions or data to be loaded intoDocket No. TP388527WO1 computing system 400. Such instrumentalities may include, for example, a removable storage unit and an interface, such as a program cartridge and cartridge interface, a removable memory (for example, a flash memory or other removable memory module) and memory slot, and other removable storage units and interfaces that allow software and data to be transferred from the storage device 410 to computing system 400.

[0073] Computing system 400 can also include a communications interface 418. Communications interface 418 can be used to allow software and data to be transferred between computing system 400 and external devices. Examples of communications interface 418 can include a modem, a network interface (such as an Ethernet or other NIC card), a communications port (such as for example, a USB port, a RS-232C serial port), a PCMCIA slot and card, Bluetooth, etc. Software and data transferred via communications interface 418 are in the form of signals which can be electronic, electromagnetic, optical or other signals capable of being received by communications interface 418. These signals may be transmitted and received by communications interface 418 via a channel such as a wireless medium, wire or cable, fiber optics, or other communications medium. Some examples of a channel include a phone line, a cellular phone link, an RF link, a network interface, a local or wide area network, and other communications channels.

[0074] Computing system 400 may be coupled via bus 402 to a display 412, such as a cathode ray tube (CRT) or liquid crystal display (LCD), for displaying information to a computer user. An input device 414, including alphanumeric and other keys, is coupled to bus 402 for communicating information and command selections to processor 404, for example. An input device may also be a display, such as an LCD display, configured with touchscreen input capabilities. Another type of user input device is cursor control 416, such as a mouse, a trackball or cursor direction keys for communicating direction information and command selections to processor 404 and for controlling cursor movement on display 412. This input device typically has two degrees of freedom in two axes, a first axis (e.g., x) and a second axis (e.g., y), that allows the device to specify positions in a plane. Computing system 400 provides data processing and provides a level of confidence for such data. Consistent with certain implementations of embodiments of the present teachings, data processing and confidence values are provided by computing system 400 in response to processor 404 executing one or moreDocket No. TP388527WO1 sequences of one or more instructions contained in memory 406. Such instructions may be read into memory 406 from another computer-readable medium, such as storage device 410. Execution of the sequences of instructions contained in memory 406 causes processor 404 to perform the process states described herein. Alternatively, hard-wired circuitry may be used in place of or in combination with software instructions to implement embodiments of the present teachings. Thus, implementations of embodiments of the present teachings are not limited to any specific combination of hardware circuitry and software.

[0075] The term "computer-readable medium" and “computer program product” as used herein generally refers to any media that is involved in providing one or more sequences or one or more instructions to processor 404 for execution. Such instructions, generally referred to as “computer program code” (which may be grouped in the form of computer programs or other groupings), when executed, enable the computing system 400 to perform features or functions of embodiments of the present invention. These and other forms of non-transitory computer- readable media may take many forms, including but not limited to, non-volatile media, volatile media, and transmission media. Non-volatile media includes, for example, solid state, optical or magnetic disks, such as storage device 410. Volatile media includes dynamic memory, such as memory 406. Transmission media includes coaxial cables, copper wire, and fiber optics, including the wires that comprise bus 402.

[0076] Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, or any other magnetic medium, a CD-ROM, any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, a RAM, PROM, and EPROM, a FLASH-EPROM, any other memory chip or cartridge, a carrier wave as described hereinafter, or any other medium from which a computer can read.

[0077] Various forms of computer readable media may be involved in carrying one or more sequences of one or more instructions to processor 404 for execution. For example, the instructions may initially be carried on magnetic disk of a remote computer. The remote computer can load the instructions into its dynamic memory and send the instructions over a telephone line using a modem. A modem local to computing system 400 can receive the data on the telephone line and use an infra-red transmitter to convert the data to an infra-red signal. AnDocket No. TP388527WO1 infra-red detector coupled to bus 402 can receive the data carried in the infra-red signal and place the data on bus 402. Bus 402 carries the data to memory 406, from which processor 404 retrieves and executes the instructions. The instructions received by memory 406 may optionally be stored on storage device 410 either before or after execution by processor 404.

[0078] It will be appreciated that, for clarity purposes, the above description has described embodiments of the invention with reference to different functional units and processors. However, it will be apparent that any suitable distribution of functionality between different functional units, processors or domains may be used without detracting from the invention. For example, functionality illustrated to be performed by separate processors or controllers may be performed by the same processor or controller. Hence, references to specific functional units are only to be seen as references to suitable means for providing the described functionality, rather than indicative of a strict logical or physical structure or organization.

[0079] Distributed System

[0080] FIG. 5 illustrates an exemplary distributed network system according to various embodiments described herein.

[0081] Some of the elements of a typical Internet network configuration 500 are shown in FIG. 5, where a number of client machines 502 possibly in a remote local office, are shown connected to a gateway / hub / tunnel-server / etc. 510 which is itself connected to the internet 508 via some internet service provider (ISP) connection 510. Also shown are other possible clients 512 similarly connected to the internet 508 via an ISP connection 514, with these units communicating to possibly a central lab or office, for example, via an ISP connection 516 to a gateway / tunnel-server 518 which is connected 520 to various enterprise application servers 522 which could be connected through another hub / router 526 to various local clients 530. Any of these servers 522 could function as a development server for the analysis of potential content management and delivery design solutions as described in the present invention, as more fully described below.

[0082] MicroscopeDocket No. TP388527WO1

[0083] FIG. 6 illustrates a diagram of an inverted fluorescent optical system according to various embodiments described herein.

[0084] A drawing of an inverted fluorescent optical system 600 according to various embodiments described herein is shown in FIG. 6. Reaction site 602 is being analyzed by system 600. Light from light source 604 is directed through an illumination tube lens 606 to filter cube 608. Light source 604 may be a LED / Laser Pumped Phosphor (LPP) light source. Filter cube 608 includes an excitation filter, dichroic filter, and emission filter. The excitation filter transmits the light to dichroic filter of filter cube 608. The dichroic filter reflects the light through objective lens 616 to reaction site 602. The reflected light will excite the fluorescent dye to emit light that will pass through objective lens 616 through an emission filter included in filter cube 608. The emitted light passes through imaging tube lens 610 to mirror 612 and to an optical imaging sensor 614 to detect the emitted light. Objective lens 616, and imaging tube lens 610 determine the magnification of the microscope.

[0085] According to various embodiments, the optical imaging sensor may be a camera such as a CMOS, CCD, or other digital type, transferring detected light to digital signals. According to various embodiments described herein, optical imaging sensor 614 is a monochrome camera.

[0086] Further, with reference back to FIG. 2, an optical imaging sensor mount 216 connects the optical imaging sensor to the microscope body. Optical imaging sensor mount 216 is configured to allow movement during calibration alignment. When a position of the optical imaging sensor is determined by the alignment calibration according to various embodiments of the present teaching, optical imaging sensor mount may be securely locked to fix the optical imaging sensor in the best position to provide high quality images. Further, optical imaging sensor 220 may be connected to optical imaging sensor alignment fixture 218 to accurately position optical imaging sensor 220 in an optical position based on focusing metrics and tilt metrics determined by various embodiments described herein. Optical imaging sensor alignment fixture 218 may be disconnected after optical imaging sensor 220 is in the optimal position.

[0087] Optical Imaging Sensor Alignment FixtureDocket No. TP388527WO1

[0088] An example of a camera alignment fixture according to various embodiments is depicted in FIG. 7.

[0089] Optical imaging sensor Alignment Fixture 700 serves as both a holder and a precision motion device for aligning the optical imaging sensor in a desired position. In various embodiments, it includes three micrometer driven goniometers and three micrometer driven linear stages. These components enable movement in all six degrees of freedom, allowing for precise adjustments to position the optical imaging sensor accurately. The purpose of these adjustments is to ensure that the image captured by the optical imaging sensor is centered, in sharp focus, and that the optical imaging sensor is positioned as close to perpendicular to the system's optical axis as possible. This level of alignment is important to achieve optimal image quality and performance in the overall system.

[0090] Optical Imaging Sensor Mounts

[0091] As mentioned above, an optical imaging sensor mount links the optical imaging sensor to rest of microscope body. FIG. 8A, FIG. 8B, and FIG. 9 illustrate perspective views of an exemplary camera mount according to various embodiments described herein.

[0092] As the only compensator in the system the optical imaging sensor can be adjustable in six degrees of freedom according to various embodiments described herein. The optical imaging sensor mount allows these six degrees of freedom which include translation along the x, y, and z axes, as well as rotation around these axes. In various embodiments described herein, tip and tilt along the x- and y- axes and rotation along the z-axis is described. This is commonly known as pitch, yaw, and roll. The camera mount moves in conjunction with optical imaging sensor alignment fixture. This level of adjustability allows the optical imaging sensor to be positioned and oriented precisely in any desired direction such that the image in sharp focus, and that the optical imaging sensor is positioned as close to perpendicular to the system's optical axis as possible. Once the desired position is reached, the optical imaging sensor mount also allows locking the optical imaging sensor in that position using screws and spherical washers in various embodiments.Docket No. TP388527WO1

[0093] An exemplary optical imaging sensor mount is shown FIGS. 8A and 8B. In this example, optical imaging sensor mount allows independent movements of each of six degrees of freedom. This option of optical imaging sensor mount consists of three parts. The pitch and yaw are achieved by using spherical surfaces centered on the optical imaging sensor which allows true gimbal motion. The shaft and collar allow Z-linear motions and roll. The collar also has features that allow the optical imaging sensor to move in X & Y axis linearly.

[0094] FIG. 9 illustrates a perspective view of another exemplary camera mount according to various embodiments described herein. In this example, an optical imaging sensor mount utilizes a hexapod, which is a mechanical structure with six legs or limbs. The hexapod provides a stable and robust foundation for supporting the optical imaging sensor. Each leg of the hexapod is equipped with joints that can extend and contract the length of leg allowing the assembly to articulate and move in various ways. Incorporating a hexapod into the design of an adjustable optical imaging sensor mount offers significant advantages in terms of precise and versatile positioning capabilities. By leveraging these joints, the hexapod can achieve precise and controlled movements in all six degrees of freedom, enabling fine adjustments and positioning of the optical imaging sensor in any desired direction. The combination of the hexapod's mechanical structure and its limb articulation makes it an ideal choice for applications where precise optical imaging sensor positioning is important, such as in microscopy. Once the desired position is achieved each of the six legs or limbs can be locked using screws in various embodiments.

[0095] Alignment Target Fixture

[0096] FIG. 10A and FIG. 10B illustrate exemplary perspective views of an alignment target moveable stage according to various embodiments described herein.

[0097] Alignment target fixture 1000 includes a mechanical housing 1008 with features tip and tilt angular adjustability.

[0098] In various embodiments, alignment target fixture 1000 can be installed on to the microscope body at microscope end 1002 of alignment target fixture 1000. However, in otherDocket No. TP388527WO1 embodiments, alignment target fixture 1000 can be installed separately from the microscope body.

[0099] Alignment Target

[0100] A cross-sectional view of alignment target fixture 1000 is shown in FIG. 10B. A piezo stage 1004 is included in alignment target fixture 1000 and is configured to move in the z- axis perpendicular to the stage. Alignment target 1006 is installed on piezo stage 1004. In some embodiments, alignment target 1006 is a glass target with custom designed target patterns over the entire field of view. The target patterns are magnified by the microscope and imaged by the optical sensor with appropriate illumination.

[0101] With reference back to FIG. 2, illumination light source 204 provides appropriate illumination light with the desired wavelengths, intensity, and spatial and angular distribution properties to illuminate alignment target 1006 (FIG. 10B). Illumination light source 204 typically includes a light source and a light conditioner. The light source can be a white or color LED, a Xenon lamp, or other types to provide the desired light wavelengths and power. The light conditioner includes but is not limited to the combinations of liquid or fiber light guide, condenser lenses, filters, and diffusers to achieve the desired intensity and distribution of light onto the alignment target.

[0102] Another exemplary alignment target is depicted in FIG. 11A and FIG. 11B according to various embodiments described herein.

[0103] An alignment target 1102 may be a glass plate with a custom target pattern on the surface. According to various embodiments described herein, an alignment target may be made of common optical materials like fused silica or borofloat. With reference to FIG 11A, the alignment target 1102 is positioned with the patterned surface away from the objective lens 1104, to simulate the use of a cover glass or sample tray, as a biological sample would be viewed. The thickness of the glass plate and its distance from the objective lens 1104 are calculated such that the optical path length of the pattern is like that of the biologic sample in the actual microscope application. An example of the microscope application is to image a DNA microarray sample immersed in a liquid buffer held in a glass tray. The borofloat glass tray has aDocket No. TP388527WO1 thickness of 0.7 mm and the buffer has a thickness of 0.3 mm. A fused silica plate with thickness of 1 mm is a good match of the buffer and glass tray and is selected to make the alignment target.

[0104] In one example, the surface of the alignment target made of glass is coated with chrome, covering most of the area, except for a small transparent target pattern at the center. This negative alignment target has high specular reflection and a minimum optical density of OD4. The high optical density is required to increase the image contrast and reduce stray light. The transparent target pattern can be larger than the objective lens’ field of view.

[0105] An example of a target pattern on the alignment target is a pinhole array. Other types of patterns with repeated features can also be used according to various embodiments of the present teachings. Examples include checkerboard, rulings, and grids. The dimensions and pitch of the pinholes are customized based on the microscope's optical design. For example, FIG. 11B shows a pinhole array target pattern 1106 suitable for a microscope with a 10X objective lens and a camera with a 6.5 micrometer pixel size. Each pinhole is circular, with a diameter of 3 micrometers and a pitch distance of 10 micrometers. A magnified view of target pattern 1106 is shown in view 1108. The overall area of the pinhole array target pattern 1106 is 2mm x 2mm, covering the 1.2mm x 1.2mm microscope field of view. Smaller pinhole sizes and denser pitches can be used for higher magnification microscopes. In some embodiments, pinhole shape can also be square. Further, additional target patterns, such as crosshairs, picture frames, and tick marks, can be added to alignment target 1102.

[0106] Generating Focusing Metrics

[0107] According to various embodiments described herein, an optical imaging sensor generates images of an alignment target to determine focusing metrics to calibrate alignment of the microscope with the optical imaging sensor. In this way, high quality images of a biological sample can be obtained to improve the accuracy of the results.

[0108] FIG. 12 illustrates an exemplary method for generating focusing metrics according to various embodiments described herein.

[0109] As mentioned above with reference to FIG. 4, a computing system is connected to the optical sensor and piezo stage in the alignment target fixture. Alignment software may beDocket No. TP388527WO1 installed on the computing system. In some embodiments, alignment software may be accessed via a network on a distributed system. The alignment software can control the optical sensor and the piezo stage in the alignment target fixture. Further, a computing system may stream images of the alignment target and conduct real-time image analysis to evaluate the image quality. A user interface can display focusing metrics based on the image analysis results to the user. Moreover, alignment software can provide step-by-step guidance to the user to assist in aligning the system.

[0110] In the example shown in FIG. 12, a method for processing the image of pinhole array and generating a heatmap to represent the focusing quality and variation over the field of view is shown. As mentioned above, other target patterns including repeating features, such as the pinhole array used in this example, may also be used according to various embodiments. In step 1202, a portion of an image of a target pattern is shown. In this example, target pattern is a pinhole array.

[0111] From an image of the pinhole array, portions of the image are selected to analyze single pinholes. Individual pinholes are identified as bright spots, and a pixel area is assigned for each pinhole and excluded adjacent pinholes. For example, a 3-micrometer diameter, a 10- micrometer pitch pinhole array is suitable for aligning a microscope with 10X magnification and a camera with a 6.5 micrometer pixel size. As such, a 16x16 or 18x18 pixel area where the pinhole is centered is suitable for one pinhole in this example.

[0112] By analyzing an image of a single pinhole, a single value image quality result is generated representing the local imaging quality. In the example shown in FIG. 12, after a pixel area including a single pinhole is identified, a 2-dimensional (2D) Fourier transform is then applied to the pixel area to calculate the pinhole image's spatial domain performance, as shown in step 1204. A sharper pinhole image containing more high spatial frequency information will result in a wider Fourier transform. Conversely, a blurry pinhole image with lens aberration will have a narrower Fourier transform due to the loss of high spatial frequency information.

[0113] In step 1206, the Fourier transform result is normalized and integrated to a single value, representing the overall image performance. A cross-section of the 2D Fourier transform is shown here for illustration, but the actual normalization and integration are performed in 2D.Docket No. TP388527WO1 This process of identifying a single pinhole, assigning a pixel area for a pinhole, performing 2D Fourier transform, and normalizing and integrating the 2D Fourier transform to a single value is applied to all pinholes within the field of view. In step 1208, a heatmap is generated based on the values of all the pinholes in the field of view. To reduce local noise and smooth the heatmap, the image can be divided into multiple bins with equal pixel numbers. The analyzed values of the pinholes within each bin can be averaged or summarized to a single value. Then a heatmap is generated based on the values of all the bins. In the example shown in FIG. 12, cooler colors like blue and green represent lower image quality, while warmer colors like orange and red represent higher image quality. The heatmap is presented to the user interface such as a computer screen, so the user can observe the overall image performance.

[0114] Below is an example of using a Fourier Transform to generate a heatmap, according to various embodiments described herein. Using Fourier Transforms, a focus quality is determined for each feature in a target pattern. The example below describes determining a focus quality for each pinhole in a target pattern of a pinhole array.

[0115] Fourier Transform Example

[0116] The analytic Fourier Transform of a function g of two variables x and y is ^ ^^^ = ^ ^ ^^^^^^^^^

[0117] The , highly efficient offspring, the fast Fourier transform (FFT) is used for modeling Fourier optics problems on the computer.

[0118] For a portion of the image containing a single pinhole ^^^^, ^^ in a pixel area withMxM pixels, the DFT of the single pinhole image is: ' ' ^^ ^%&Docket No. TP388527WO1

[0119] The Fourier transform is then normalized to its peak.

[0120] The normalized Fourier transform is integrated into a single value to represent the focus quality of the pinhole

[0121] The single value for each pinhole is used to generate a heatmap illustrating the focus quality.

[0122] Next, to derive quantified metrics from the heatmap, the heatmap is fitted to a distribution profile. With reference back to FIG. 12, in step 1210, a 2D Gaussian profile is used. Multiple focusing metrics can be obtained from this fitting, including fit error, center offset, width, aspect ratio, and peak amplitude. Fit error represents the average fit error as a percentage of the Gaussian's amplitude. Center offset indicates the offset of the Gaussian's center from the image's center, expressed as a percentage of the image width. Width is the standard deviation width of the Gaussian divided by the image width. Aspect ratio is the ratio between the longer and shorter axis of the Gaussian. Peak amplitude refers to the Gaussian's highest value. The focusing metrics are displayed on the user interface such as a computer screen. When user makes any change to the alignment including moving the alignment target position or moving the imaging sensor position, the heatmap and the focusing metrics are both updated. The user then uses the following guidelines to select the best alignment position. Fit error and center offset need to be as low as possible. Peak amplitude needs to be as high as possible. Width needs to be high and aspect ratio needs to be as close to 1.0, but they might need to be balanced in some cases.Docket No. TP388527WO1

[0123] Heatmap Fitting Method (2D Gaussian) and Focus Metrics Example

[0124] Two-dimensional elliptical Gaussian function is expressed as: ^^^, ^^ = ,^^^-−. / ^^ − ^0^1 + 22^^ − ^0^^^ − ^0^ + 3^^ − ^0^145=−2:1^ 2:1^^sin 9^1 ^cos 9^13 =2:1 +^ 2:1^Where (x0, y0) is the center of the Gaussian function, A is the peak of the Gaussian profile, θ is the rotation angle, σxis standard deviation in x and the σyis standard deviation in y.

[0125] 1. Heatmap Fitting

[0126] Let H(x, y) be the heatmap for an image size or binned image size of (Wx, Wy), and W is the larger number of Wxand Wy. Fit H(x,y) with a 2D Gaussian function: =^^, ^^ = ^^^, ^^ + ^^^, ^^where e(x, y) is the fit error for each pixel.

[0127] The fitting should minimize the total error: ?A ?@

[0128] 2. The Focus Metrics can be defined as:

[0129] A. Average Fit error:Docket No. TP388527WO1 B1 ∑?A ∑?@D^D^ ^)* ^)* |^^^, ^^| FG,

[0130] B. Center Offset:D11 −^ + B D% ^ − ^

[0131] C. Width:max ^:^, :^^M D

[0132] D. Aspect Ratio:max ^:^ , :^^G

[0133] Tilt Metrics

[0134] According to various embodiments described herein, adjustment to the tilt of the optical sensor may also be determined to further improve image quality.

[0135] FIGS. 13A-13B depict an optical imaging sensor plane 1304 and an image surface 1302 in good alignment according to various embodiments described herein. FIG. 13B illustrates another view of image surface 1302 and optical imaging sensor plane 1304.

[0136] Image surface 1302 is the combination of best focuses for different field positions. It is typically slightly curved due to field curvature of the lenses. Image surface can be calculated by taking a set of images when moving the optical imaging sensor along the z axis, or alternatively moving the alignment target along the z axis and determining the best z position to achieve the highest image quality value for each field position. This is referred to as a z-stack method according to various embodiments described herein. The z-stack method can also be used to analyze the tilt of the image surface with respect to the optical imaging sensor plane byDocket No. TP388527WO1 analyzing the variation of the image surface along x axis (e.g. from left to right of the field) and along y axis (e.g. from top to bottom of the field).

[0137] FIGS. 14A-14C shows the non-tilted and tilted image surfaces. As shown in FIG. 14A, optical image sensor plane 1404 is aligned with image surface 1402. FIG. 14B depicts image surface 1402 tilted in one direction around the x-axis, while FIG. 14C depicts image plane 1402 tilted in the other direction around the x-axis. By moving the optical imaging sensor plane to different angles and calculating the corresponding image surface tilt metrics, the position resulting in the least image surface tilt can be found as the example FIG. 14A, and a best focused image can be achieved.

[0138] A z-stack is a stack of images taken along the z axis with same step size. The z-stack images can be acquired by moving the alignment target along the z axis with a fixed step size and taking one image with a fixed exposure time at each step. For a microscope system, the step size for the alignment target is typically in micrometer or sub micrometer. Alternatively, the z- stack images can be acquired by moving the camera along the z axis with a fixed step size and taking one image with a fixed exposure time at each step. After the z-stack images are acquired, the software produces the heatmap for each image. By comparing the heatmaps, the best z position for each field position can be calculated and the best focus surface or the image surface can be created.

[0139] FIG. 15A shows image surface 1502 in 2 dimensions for illustration, but the actual image surface is in 3 dimensions. Image surface 1502 is generated by taking a z-stack image set by moving the alignment target along z axis and calculating the best focus z position for each field position. Image surface 1502 is typically curved due to filed curvature. After the image surface is generated, a best fitted plane 1506 can be found by minimizing the difference in z between image surface 1502 and fitted plane 1506. Fitted plane 1506 represents the best optical imaging sensor position that aligns with the image to achieve the best focus. In this example, the z-stack image set is generated by moving the alignment target, so the z-position of the fitted plane 1506 reflects the best z-position of the alignment target. As illustrated in FIG. 15, the slope of best fitted plane 1506 in the y-direction is dzdy, the tilt metric along x-axis. The slope of best fitted plane 1506 in the x-direction is dzdx, the tip metric along y-axis. The tip-tilt metrics dzdxDocket No. TP388527WO1 and dzdy represent how tilted the image is for the given optical imaging sensor orientation. When the microscope system is aligned, the dzdx (tilt along Y-axis) and dzdy (tip along X-axis) should be close to zero.

[0140] FIG. 15B illustrates determining the imaging sensor orientation to reduce or minimize image tilt using a z-sweep method according to various embodiments described herein. Broadly, in this method, it is determined which optical imaging sensor orientation minimizes image tilt along X-axis. When the optical imaging sensor 1504 angular orientation changes along the X- axis, tilt metric dzdy calculated from the z-stack also changes. Optical imaging sensor 1504 can be swept to at a few different angular orientations along X-axis. For each orientation, a z-stack image set is collected for generating image surface 1502 and the corresponding dzdy is calculated. It has been found that dzdy is linear to the imaging sensor’s tilt angle. As such, the intersect where dzdy equals 0 is the tilt angle what minimizes the image tilt along the X-axis. Similarly, the optical imaging sensor angular orientation along the Y-axis which minimizes the image tip can be found by sweeping the optical imaging sensor angular orientation along the Y- axis.

[0141] Method of Optical Imaging Sensor Alignment

[0142] As discussed above, several methods are used to determine the best alignment for the optical sensor and the microscope in a biological analysis instrument according to various embodiments described herein. FIG. 16 illustrates an exemplary flowchart of an overall method of calibrating optical imaging sensor alignment according to various embodiments described herein.

[0143] In step 1602, a microscope body is mounted to an alignment stage and an optical imaging sensor is mounted to an optical imaging sensor alignment fixture. The alignment stage holds the microscope body parallel to the optical table, and roughly aligns the microscope body to the optical imaging sensor when the optical imaging sensor alignment fixture is at its nominal position. The optical imaging sensor mount is loosely connected to the microscope body so that the optical imaging sensor position can be adjusted and after alignment the optical imaging sensor mount is ready to be locked.Docket No. TP388527WO1

[0144] In step 1604, the optical imaging sensor rotation is corrected to minimize image rotation. One method of doing this is using a leveler to make the optical imaging sensor body parallel to the microscope body. Alternatively, imaging-based methods can be used to reduce the optical imaging sensor rotation with reference to the microscope body. One example is using a rotation target which has minimum rotation with reference to the microscope body.

[0145] In step 1606, the autocollimator is aligned to the reference surface in the alignment. Typically, the mounting surface of the microscope objective lens is selected as the reference surface. The back surface of a mirror is attached to the reference surface. The said mirror may have surface flatness of lambda / 10 or better and parallelism of 0.01 degree or better. The autocollimator can be physically aligned to the said mirror when the beam of light from the autocollimator normally incident to the said mirror. Alternatively, the autocollimator can be zeroed to the said mirror when the zeroing function is available. After the alignment of the autocollimator, the mirror is removed.

[0146] In step 1608, the beam of light from the autocollimator passes through the microscope body and incident to the optical imaging sensor. By making angular adjustment in the optical imaging sensor alignment fixture, the optical imaging sensor is angularly aligned to the autocollimator when the beam of light from autocollimator normally incidents to the optical imaging sensor. Step 1508 pre-aligns the optical imaging sensor angularly so that the sensor is parallel to the reference surface.

[0147] After pre-alignment of the optical imaging sensor angularly, the objective lens and tube lens is assembled to the microscope body in step 1610.

[0148] In step 1612, a centration target is used to pre-align the optical imaging sensor’s linear position. One example of the alignment target is a pinhole array at the working distance of the objective lens and mechanically centered to the objective lens. With appropriate illumination, the pinhole is imaged on the optical imaging sensor. By making linear adjustment of the optical imaging sensor alignment fixture, the optical imaging sensor is moved in X and Y axis until the image of the pinhole is at the center of the sensor.Docket No. TP388527WO1

[0149] In step 1614, the alignment target fixture is installed. The alignment target is positioned close to the working distance of the objective lens. The alignment target is negative type with relatively high surface reflection. The angular adjuster is changed for the alignment target fixture until the alignment target is angularly aligned to the autocollimator when beam of light from the autocollimator normally incidents on the alignment target. This step ensures that the alignment target is parallel to the reference surface, or the objective lens.

[0150] In step 1616, the best focus is found at the desired magnification. Provides appropriate illumination to the alignment target for imaging. By moving the piezo in the alignment target fixture in Z direction and moving the optical imaging sensor in Z direction, the image can be brought to focus. The alignment software processes the image of the pinhole array and displays the corresponding heatmap and the magnification. The piezo and the optical imaging sensor are adjusted in Z direction until the magnification meets requirement and the focusing metrics of the heatmap meet requirements on fit error, peak amplitude, and width.

[0151] The heatmap found in Step 1618 may not be centered due to decentration and tip / tilt of the optical and mechanical components. Step 1618 moves the optical imaging sensor in X and Y to make the center offset of the heatmap to minimum.

[0152] In step 1620, a z-stack is collected and analyzed to evaluate the image tilt for the current optical imaging sensor orientation. The image tilt metrics dzdx and dzdy can be calculated from the z-stack. The absolute values of dzdx and dzdy need to be smaller than certain value. If the image tilt is small enough and all the focus metrics at the best z position meet requirement, the best optical imaging sensor position is found. Then the microscope system is considered as aligned, and the optical imaging sensor mount can be locked. If the absolute value of dzdx or dzdy is higher than the requirement, the image tilt needs to be compensated.

[0153] Step 1622 searches for the best optical imaging sensor angular orientation to compensate for the image tilt using the Z- sweep method. The optical imaging sensor is angularly adjusted to several orientations by tipping along X-axis, and Z-Stack is collected for each orientation. The angular position which minimizes the image tilt metric dzdy can be calculated, representing the suggested optical imaging sensor tip along X-axis Similarly, the optical imaging sensor is angularly adjusted to several orientations by tilting along Y-axis, andDocket No. TP388527WO1 Z-Stack is collected for each orientation. The angular position which minimizes the image tilt metric dzdx can be calculated, representing the suggested optical imaging sensor tilt along Y- axis. Then the optical imaging sensor is adjusted to the suggested image tilt minimized orientation.

[0154] Step 1624 is the post Z-Sweep adjustment. The optical imaging sensor is adjusted linearly in X and Y to center the heatmap.

[0155] Step 1626 uses z-stack analysis to evaluate the image tilt same as in step 1620. If the image tilt calculated from z-stack is smaller than requirement, the optical imaging sensor mount can be locked. Otherwise, the z-sweep method can be repeated to further improve the optical imaging sensor orientation.

[0156] Step 1628 locks the optical imaging sensor mount by tightening the screws, so the optical imaging sensor position is fixed to the microscope body.

[0157] While locking the optical imaging sensor mount, there could be small amounts of optical imaging sensor position change. Thus, step 1630 performs the final inspection using Z- Stack method and the heatmap method. If all the specifications are met, the microscope system alignment is completed in step 1632.

[0158] Examples

[0159] The following numbered examples are embodiments: 1. A method for aligning an optical imaging sensor, the method comprising: receiving an image of a target pattern of an alignment target positioned near a microscope objective lens; determining an image quality for each element of the target pattern; generating a heatmap for the image based on the determined image quality for each element of the target pattern, wherein the heatmap indicates focusing quality and variation over a field-of-view of the objective lens;Docket No. TP388527WO1 determining focusing metrics based on fitting the heatmap to a distribution profile; and providing the focusing metrics to a user, wherein the focusing metrics are used to adjust alignment of the optical imaging sensor to improve image quality. 2. The method of example 1, wherein determining the image quality for each element of the target pattern includes: identifying a portion of the image including an individual element of the target pattern; and determining a Fourier transform result to the identified portion of the image for each element of the target pattern. 3. The method of examples 1 or 2, wherein the focusing metrics include at least one of the following: fit error, center offset, width, aspect ratio, and peak amplitude. 4. The method of any of the examples 1 to 3, wherein the distribution profile is a 2D Gaussian profile. 5. The method of any of the examples 1 to 4, further comprising: receiving a z-stack image set of images of the target pattern, wherein the z-stack image set includes at least a first image of the alignment target at a first z-position and a second image of the alignment target at a second z-position; generating a heatmap for the first image and the second image of the z-stack image set based on the determined image quality for each element of the target pattern; comparing the heatmap of the first image and the heatmap of the second image to generate tilt metrics; and providing the tilt metrics to a user, wherein the tilt metrics are used to further adjust alignment of the optical imaging sensor to improve image quality. 6. The method of any of the examples 1 to 5, further comprising:Docket No. TP388527WO1 receiving a z-sweep image set of images of the target pattern, wherein the z-sweep image set includes at least a first z-stack image set of the alignment target at a first angle of the optical imaging sensor along an x-axis, and a second z-stack image set of the alignment target generated at a second angle of the optical imaging sensor along the x-axis; generating a first heatmap for the first z-stack image set and a second heatmap for the second z-stack image set based on the determined image quality for each element of the target pattern; comparing the first and second heatmap to generate tilt angle metrics; and providing the tilt angle metrics to a user, wherein the tilt angle metrics are used to further adjust alignment of the optical imaging sensor to improve image quality. 7. The method of any of the examples 1 to 6, wherein the z-sweep image set includes at least a third z-stack image set of the alignment target at a first angle of the optical imaging sensor along an y-axis, and a fourth z-stack image set of the alignment target generated at a second angle of the optical imaging sensor along the y-axis. 8. The method of any of the examples 1 to 7, the method further comprising: generating a third heatmap for the third z-stack image set and a fourth heatmap for the fourth z-stack image set based on the determined image quality for each element of the target pattern, wherein the tilt metrics are further based on the third and fourth heatmaps. 9. A computer-readable medium encoded with computer-readable instructions, which when executed by a processor of a computer, causes the computer to carry out the method of any one of the examples 1 to 8. 10. A system comprising a processor, and a storage medium storing instruction, which when executed by a processor, causes the system to carry out the method of any one of examples 1 to 8. 11. A system for aligning an optical imaging sensor, the system comprising: an alignment target positioned near a microscope objective lens, wherein the alignment target includes a target pattern;Docket No. TP388527WO1 a processor configured to: receive an image of the target pattern, determine an image quality for each element of the target pattern, generate a heatmap for the image based on the determined image quality for each element of the target pattern, wherein the heatmap indicates focusing quality and variation over a field-of-view of the objective lens, determine focusing metrics based on fitting the heatmap to a distribution profile, and provide the focusing metrics to a user, wherein the focusing metrics are used to adjust alignment of the optical imaging sensor to improve image quality; and an optical imaging sensor fixture configured to adjust the position of the optical imaging sensor based on the focusing metrics. 12. The system of example 11, wherein the target pattern includes a pinhole array, wherein the dimensions of the pinhole array are based on an optical design of the microscope and optical imaging sensor. 13. The system of examples 11 or 12, wherein the optical design includes a 10x objective lens and an optical imaging sensor pixel size of 6.5 micrometers, and wherein each pinhole of the pinhole array has a diameter of 3 micrometers and a pitch distance of 10 micrometers. 14. The system of any of the examples 11 to 13, wherein the target pattern is on a surface of a glass plate and positioned away from the objective lens. 15. The system of any of the examples 11 to 14, wherein the processor is further configured to determine the image quality for each element of the target pattern by:Docket No. TP388527WO1 identifying a portion of the image including an individual element of the target pattern; and determining a Fourier transform result to the identified portion of the image for each element of the target pattern. 16. The system of any of the examples 11 to 15, wherein the focusing metrics include at least one of the following: fit error, center offset, width, aspect ratio, and peak amplitude. 17. The system of any of the examples 11 to 16, wherein the processor is further configured to: receive a z-stack image set of images of the target pattern, wherein the z-stack image set includes at least a first image of the alignment target at a first z-position and a second image of the alignment target at a second z-position, generate a heatmap for the first image and the second image of the z-stack image set based on the determined image quality for each element of the target pattern, compare the heatmap of the first image and the heatmap of the second image to generate tilt metrics, and provide the tilt metrics to a user, wherein the tilt metrics are used to further adjust alignment of the optical imaging sensor to improve image quality. 18. The system of any of the examples 1 to 17, wherein the processor is further configured to: receive a z-stack image set of images of the target pattern, wherein the z-stack image set includes at least a first image of the alignment target at a first angle in an axis and a second image of the alignment target generated at a second angle in the axis, generate a heatmap for the first image and the second image of the z-stack image set based on the determined image quality for each element of the target pattern,Docket No. TP388527WO1 compare the heatmap of the first image and the heatmap of the second image to generate tilt angle metrics, and provide the tilt angle metrics to a use, wherein the tilt angle metrics are used to further adjust alignment of the optical imaging sensor to improve image quality. 19. The system of example 18, wherein the axis is a y-z axis. 20. The system of example 18, wherein the axis is a x-z axis. 21. A method for aligning an optical imaging sensor, the method comprising: receiving an image of a target pattern of an alignment target positioned near a microscope objective lens; determining an image quality for each element of the target pattern; generating a heatmap for the image based on the determined image quality for each element of the target pattern, wherein the heatmap indicates focusing quality and variation over a field-of-view of the objective lens; determining focusing metrics based on fitting the heatmap to a distribution profile; generating a set of heatmaps for the target pattern, wherein each heatmap of the set is generated at a different z-position of the optical imaging sensor; determining tilt metrics based on the set of heatmaps; and providing the focusing metrics and the tilt metrics to a user, wherein the focusing metrics and the tilt metrics are used to adjust alignment of the optical imaging sensor to improve image quality.

Claims

Docket No. TP388527WO1 CLAIMS What is claimed is:

1. A method for aligning an optical imaging sensor, the method comprising: receiving an image of a target pattern of an alignment target positioned near a microscope objective lens; determining an image quality for each element of the target pattern; generating a heatmap for the image based on the determined image quality for each element of the target pattern, wherein the heatmap indicates focusing quality and variation over a field-of-view of the objective lens; determining focusing metrics based on fitting the heatmap to a distribution profile; and providing the focusing metrics to a user, wherein the focusing metrics are used to adjust alignment of the optical imaging sensor to improve image quality.

2. The method of claim 1, wherein determining the image quality for each element of the target pattern includes: identifying a portion of the image including an individual element of the target pattern; and determining a Fourier transform result to the identified portion of the image for each element of the target pattern.

3. The method of claims 1 or 2, wherein the focusing metrics include at least one of the following: fit error, center offset, width, aspect ratio, and peak amplitude.

4. The method of any of the claims 1 to 3, wherein the distribution profile is a 2D Gaussian profile.

5. The method of any of the claims 1 to 4, further comprising:Docket No. TP388527WO1 receiving a z-stack image set of images of the target pattern, wherein the z-stack image set includes at least a first image of the alignment target at a first z-position and a second image of the alignment target at a second z-position; generating a heatmap for the first image and the second image of the z-stack image set based on the determined image quality for each element of the target pattern; comparing the heatmap of the first image and the heatmap of the second image to generate tilt metrics; and providing the tilt metrics to a user, wherein the tilt metrics are used to further adjust alignment of the optical imaging sensor to improve image quality.

6. The method of any of the claims 1 to 5, further comprising: receiving a z-sweep image set of images of the target pattern, wherein the z-sweep image set includes at least a first z-stack image set of the alignment target at a first angle of the optical imaging sensor along an x-axis, and a second z-stack image set of the alignment target generated at a second angle of the optical imaging sensor along the x-axis; generating a first heatmap for the first z-stack image set and a second heatmap for the second z-stack image set based on the determined image quality for each element of the target pattern; comparing the first and second heatmap to generate tilt angle metrics; and providing the tilt angle metrics to a user, wherein the tilt angle metrics are used to further adjust alignment of the optical imaging sensor to improve image quality.

7. The method of any of the claims 1 to 6, wherein the z-sweep image set includes at least a third z-stack image set of the alignment target at a first angle of the optical imaging sensor along an y-axis, and a fourth z-stack image set of the alignment target generated at a second angle of the optical imaging sensor along the y-axis.

8. The method of any of the claims 1 to 7, the method further comprising: generating a third heatmap for the third z-stack image set and a fourth heatmap for the fourth z-stack image set based on the determined image quality for each element of the target pattern, wherein the tilt metrics are further based on the third and fourth heatmaps.Docket No. TP388527WO1 9. A computer-readable medium encoded with computer-readable instructions, which when executed by a processor of a computer, causes the computer to carry out the method of any one of the claims 1 to 8.

10. A system comprising a processor, and a storage medium storing instruction, which when executed by a processor, causes the system to carry out the method of any one of claims 1 to 8.

11. A system for aligning an optical imaging sensor, the system comprising: an alignment target positioned near a microscope objective lens, wherein the alignment target includes a target pattern; a processor configured to: receive an image of the target pattern, determine an image quality for each element of the target pattern, generate a heatmap for the image based on the determined image quality for each element of the target pattern, wherein the heatmap indicates focusing quality and variation over a field- of-view of the objective lens, determine focusing metrics based on fitting the heatmap to a distribution profile, and provide the focusing metrics to a user, wherein the focusing metrics are used to adjust alignment of the optical imaging sensor to improve image quality; and an optical imaging sensor fixture configured to adjust the position of the optical imaging sensor based on the focusing metrics.Docket No. TP388527WO1 12. The system of claim 11, wherein the target pattern includes a pinhole array, wherein the dimensions of the pinhole array are based on an optical design of the microscope and optical imaging sensor.

13. The system of claims 11 or 12, wherein the optical design includes a 10x objective lens and an optical imaging sensor pixel size of 6.5 micrometers, and wherein each pinhole of the pinhole array has a diameter of 3 micrometers and a pitch distance of 10 micrometers.

14. The system of any of the claims 11 to 13, wherein the target pattern is on a surface of a glass plate and positioned away from the objective lens.

15. The system of any of the claims 11 to 14, wherein the processor is further configured to determine the image quality for each element of the target pattern by: identifying a portion of the image including an individual element of the target pattern; and determining a Fourier transform result to the identified portion of the image for each element of the target pattern.

16. The system of any of the claims 11 to 15, wherein the focusing metrics include at least one of the following: fit error, center offset, width, aspect ratio, and peak amplitude.

17. The system of any of the claims 11 to 16, wherein the processor is further configured to: receive a z-stack image set of images of the target pattern, wherein the z-stack image set includes at least a first image of the alignment target at a first z-position and a second image of the alignment target at a second z-position, generate a heatmap for the first image and the second image of the z-stack image set based on the determined image quality for each element of the target pattern,Docket No. TP388527WO1 compare the heatmap of the first image and the heatmap of the second image to generate tilt metrics, and provide the tilt metrics to a user, wherein the tilt metrics are used to further adjust alignment of the optical imaging sensor to improve image quality.

18. The system of any of the claims 1 to 17, wherein the processor is further configured to: receive a z-stack image set of images of the target pattern, wherein the z-stack image set includes at least a first image of the alignment target at a first angle in an axis and a second image of the alignment target generated at a second angle in the axis, generate a heatmap for the first image and the second image of the z-stack image set based on the determined image quality for each element of the target pattern, compare the heatmap of the first image and the heatmap of the second image to generate tilt angle metrics, and provide the tilt angle metrics to a use, wherein the tilt angle metrics are used to further adjust alignment of the optical imaging sensor to improve image quality.

19. The system of claim 18, wherein the axis is a y-z axis.

20. The system of claim 18, wherein the axis is a x-z axis.

21. A method for aligning an optical imaging sensor, the method comprising: receiving an image of a target pattern of an alignment target positioned near a microscope objective lens; determining an image quality for each element of the target pattern; generating a heatmap for the image based on the determined image quality for each element of the target pattern, wherein the heatmap indicates focusing quality and variation over a field-of-view of the objective lens; determining focusing metrics based on fitting the heatmap to a distribution profile;Docket No. TP388527WO1 generating a set of heatmaps for the target pattern, wherein each heatmap of the set is generated at a different z-position of the optical imaging sensor; determining tilt metrics based on the set of heatmaps; and providing the focusing metrics and the tilt metrics to a user, wherein the focusing metrics and the tilt metrics are used to adjust alignment of the optical imaging sensor to improve image quality.

Images