Custom Modules Research Articles

Image Processing Test Bench for Robot Vision Using C#

Purpose: Nowadays, image processing is a well-known technological term. In some of the industries, it has practical needs. It is an essential tool for the process and robotic industry. Various popular frameworks and libraries are available to process the image. The OpenCV is one of the best and popular libraries for image processing. It was originally written in C++ by Intel. Now various wrappers are available to implement into the different programming languages. The OpenCvSharp is the wrapper of OpenCV. Those who are familiar with C# can use it. The new researcher who wants to integrate image processing into their project takes some time for setup, function writing, and integration. Here we created a test bench application for Image processing demonstration. It has been made with some usual function to process the image. It was created using visual studio 2022 and OpenCvSharp wrapper in C# language. The researcher can learn about various image processing algorithms without writing any code or giving little bits of effort. The complete project is available on GitHub. Anyone can download, experiment, and integrate into their project without any issue. Design/Methodology/Approach: We created a GUI (Graphical User Interface) based C# application. Using Nuget Package manager, installed two OpenCV wrapper packages. To invoke several functions, we add some buttons, and for changing the method’s parameter, we integrate some text boxes. We created some abstraction layers Between the OpenCvSharp wrapper and GUI. We made our custom module as portable as possible so that our researchers could easily incorporate it into their project. Findings/result: This unique image processing test bench is designed for new researchers trying to integrate image processing capability into their research work. It can take still images or moving images through the connected webcam, automatically sending the various commands and promptly observing the result. Originality/Value: This test bench has been arranged uniquely for the researcher. It might have some value to their research work. The unique feature like automatic trigger can help them send the series of commands without repeatedly typing or pressing the button to see the result. Paper Type: Experiment-based Research

Development and evaluation of an online integrative histology module: simple design, low-cost, and improves pathology self-efficacy

ABSTRACT Integration of core concepts is an important aspect of medical curriculum enhancement. Challenges to improving integration include the risk of curtailing the basic sciences in the process and the push to decrease contact hours in medical curricula. Self-paced learning tools can be developed that deliberately relate basic and clinical sciences to aid students in making interdisciplinary connections. The purpose of this project was to develop, implement, and evaluate a self-paced learning module that would be applicable to integration of different disciplines in medical education. The module was intended to improve integration between histology and anatomic pathology before a respiratory pathology laboratory session. Qualtrics XM, a survey software commonly available at educational institutions, was used in a novel manner to create the module. Module activities included pre- and post-module quizzes; four short videos emphasizing normal histological features and recalling associated pathologies; three categorization activities designed for students to recognize normal versus abnormal characteristics of lung specimens; and post-activity feedback. Preliminary data from first-year medical students showed that post-module quiz scores were significantly higher than pre-module quiz scores (p < 0.001) and that module users’ pre-laboratory pathology self-efficacy was significantly higher than non-users (p < 0.05). These data suggest that module use facilitated short-term knowledge gain and improved pathology self-efficacy before the laboratory session. Online modules can be developed affordably using Qualtrics XM to integrate anatomical sciences with other disciplines, while providing students interactive learning resources without increasing contact hours. The module presented in this report focused on normal versus abnormal morphology, guiding students through recognizing the continuum from healthy to disease states before learning about the pathologies more in depth. A similar module design would likely be effective in integrating other disciplines in medicine, especially in disciplines that require recognition of changes in morphology.

Monitoring the Short-term Variations in the Stability of the Nigerian GNSS CORS Diurnal Coordinates

Positioning, based on GNSS reference network technology, is becoming a routine operation within and outside the spatial industry. The expanding user base and diverse range of applications employing this technology can impose significant expectations on the providers of reference network services. In positioning and navigation, the requirement for high accurate coordinate estimates cannot be over-emphasized. This is ensured by the provision of accurate and reliable corrections from the zero-order GNSS reference stations. It is therefore expedient to study the diurnal coordinates of such stations to guarantee reliable information for positioning and navigation applications. In this study, observation data from the Nigerian permanent GNSS continuously operating reference stations located at different states around Nigeria was processed. The hourly and diurnal (daily) coordinate solutions obtained were analysed for the purpose of monitoring the short-term stability of the network coordinates using a two-year (2012-2013) test data. The daily precise point positioning results were processed, analysed, and presented as coordinate time series using RTKPLOT. Python programming language was used to write custom modules to visualize the time series graphs at 30 seconds epochs in order to determine points and epochs where and when the condition for stability defaulted. The stations; FPNO, GEMB, and MDGR were found to be most stable in the Easting component; GEMB and MDGR were the most stable in the Northing component while in the Up component the station GEMB was the most stable. The outcome of the study will assist in detecting stations that are non-operational, performing diurnal PPP processing to detect stations that are unstable, and reporting reference stations that experience sudden coordinate changes. The developed monitoring module can be implemented by the reference stations operators as an automated program for setting up an intelligent alert system to trigger a warning whenever there is unexpected coordinate breach.

A-134 Agile Development of Virtual Reality Treatment for Spatial Neglect: Preliminary Usability and Feasibility

Abstract Objective Examine the usability and feasibility of a virtual reality (VR) treatment for persons with spatial neglect using head mounted display (HMD) and hand tracking technologies. Method Recruited from a rehabilitation hospital, 9 stroke survivors with spatial neglect (3 females; mean age = 64.2 years, SD = 9.1; 8 left neglect) participated in user testing for ongoing software development. Participants tested one of four customized treatment modules and completed the System Usability Scale, the Presence Questionnaire, and the Simulator Sickness Questionnaire. Feedback from participants were integrated into iterative prototype revisions. Module 1 (n = 7) required arm movements gradually reaching toward the neglected side of space, while the virtual hand appeared reaching straight ahead. Module 2 (n = 4) required head movements from the non-neglected to the neglected side. Module 3 (n = 6) involved head and arm movements towards both sides of space to collect objects. Module 4 (n = 2) was to stop approaching objects from a distance ahead. Results Despite reporting a lack of realism, participants preferred VR over conventional therapy. Participants felt comfortable and confident engaging in the virtual environment. Module 4 was more difficult than the other modules as participants required more practice to perform the task. Two participants reported Module 3 being tiresome, with one reporting mild shoulder pain and eye strain, and moderate sweating. However, all reported symptoms were temporary and resolved following a short break. Conclusion VR-based rehabilitation for spatial neglect using HMD and hand tracking technologies may be a viable treatment option for stroke survivors with spatial neglect. The modules benefited substantively from modifications based on participants’ feedback.

EFEKTIFITAS PEMBELAJARAN MENGGUNAKAN MODUL “TAPIS” PADA PELAJARAN KETRAMPILAN PEMBUATAN SUVENIR BAGI SISWA TUNARUNGU

Education level in SMALB aims to prepare deaf students to challenges after graduating from school. One of the skills that deaf students is souvenir skills. In the SLB N Metro, the source book or special module for souvenir skills is not yet available. To make it easier for students to make souvenirs and understanding steps of the activities, they can use module. The purpose of this study was to determine the entrepreneurial abilities of deaf students of class XII SMALB, arranging a draft of the Tapis module, determine the results of module validation and responses to modules from students. The method in this research is descriptive research and development approach. The research stage is preliminary, development and testing. The research informants were three students and five validators. The data collection techniques used observation, interview and documentation. The research results obtained data from the entrepreneurial abilities of deaf students after using the module has increased of the score. The initial draft of the module consists of 4 chapters, after being validated the module is revised into 3 chapters and changes more interest title. The students' responses included easy to read modules, attractive pictures, make it easier to make souvenir brooches. The skilled “TAPIS” module for making innovative souvenirs was successfully developed using good validation results and the module user responses could understand the contents of the module.

Contextual information enhanced convolutional neural networks for retinal vessel segmentation in color fundus images

Accurate retinal vessel segmentation is a challenging problem in color fundus image analysis. An automatic retinal vessel segmentation system can effectively facilitate clinical diagnosis and ophthalmological research. In general, this problem suffers from various degrees of vessel thickness, perception of details, and contextual feature fusion in technique. For addressing these challenges, a deep learning based method has been proposed and several customized modules have been integrated into the well-known U-net with encoder–decoder architecture, which is widely employed in medical image segmentation. In the network structure, cascaded dilated convolutional modules have been integrated into the intermediate layers, for obtaining larger receptive field and generating denser encoded feature maps. Also, the advantages of the pyramid module with spatial continuity have been taken for multi-thickness perception, detail refinement, and contextual feature fusion. Additionally, the effectiveness of different normalization approaches has been discussed on different datasets with specific properties. Finally, sufficient comparative experiments have been enforced on three retinal vessel segmentation datasets, DRIVE, CHASE_DB1, and the STARE dataset with unhealthy samples. As a result, the proposed method outperforms the work of predecessors and achieves state-of-the-art performance.

Modeling and Multi-Criteria Optimization of a Process for H2O2 Electrosynthesis

This article introduces a novel laboratory-scale process for the electrochemical synthesis of hydrogen peroxide (H2O2). The process aims at an energy-efficient, decentralized production, and a mathematical optimization of it is presented. A dynamic, zero-dimensional mathematical model of the reactor is set up in Aspen custom modeler®. The proposed model constitutes a reasonable compromise between complexity and convergence. After thoroughly determining the reaction kinetics by adjustment to experimental data, the reactor unit is embedded in an Aspen Plus® flowsheet in order to investigate its interaction with other unit operations. The downstream contains another custom module for membrane distillation. Electricity appears as a resource in the process, and optimization shows that it reaches product purities of up to 3 wt.-%. Both the process optimization and the adjustment of the reaction kinetics are treated as multi-criteria optimization (MCO) problems.

Online Deformation Characterization for Electro-Thermal-Mechanical Effect of Power Module via Confocal Methodology

Motivated by the dramatic increase of renewable energy and electric vehicle, a variety of customized power modules are rapidly designed and developed. However, it is necessary to expend a long time to examine the new power modules to ensure the reliability concerns via massive experiments, such as power cycling. The deformation characterization of the bare die has a grave impact on the failure of the power module. Therefore, to observe the weak point and presume the cycling lifetime of the power module package, the online characterization of deformation under the field application is significant. Besides, the outcomes can provide confident evidence for the finite element simulation model to conduct research on electrothermal-mechanical stress. In this letter, the mathematical model is created to understand the mechanical deformation induced by electrothermal coupling. To characterize the deformation of the power module in real-time for field application, a noninvasive confocal methodology is proposed. In addition, to confirm the feasibility of the proposed routine, an experimental setup is set up by using the front-to-front converter. The experiment results show that the maximal overall deformation occurs on the middle surface of the die while the edge of the bare die suffers minimal deformation, which corresponds to the simulation results. Besides, the overall and partial deformation errors between experimental and simulation results are within 5% and 7%, respectively.

Development of a Human Flow Generation Module for Testing Machine Learning Algorithms

This article describes a custom software module for generating human flows that is currently under research and development. Existing works on this topic are investigated. The main software developments for generating human flows and modern development tools that can help in creating the necessary module are analyzed. The choice of the development environment, language, third-party programs and modules that help in development is justified. The developed customizable module of human flows provides the movement of people, including traffic across the road, the ability to select certain groups of people to place them on the street. In addition, this module has been integrated with the virtual urban environment and transport generation module to test connectivity with other projects. Functional and load testing carried out at the end revealed some shortcomings, which were later corrected. The authors make assumptions about the integration of the module into a complex traffic model.

An Interactive Pipeline for Quantitative Histopathological Analysis of Spatially Defined Drug Effects in Tumors

Background: Tumor heterogeneity is increasingly being recognized as a major source of variability in the histopathological assessment of drug responses. Quantitative analysis of immunohistochemistry (IHC) and immunofluorescence (IF) images using biomarkers that capture spatialpatterns of distinct tumor biology and drug concentration in tumors is of high interest to the field. Methods: We have developed an image analysis pipeline to measure drug response using IF and IHC images along spatial gradients of local drug release from a tumor-implantable drug delivery microdevice. The pipeline utilizes a series of user-interactive python scripts and CellProfiler pipelines with custom modules to perform image and spatial analysis of regions of interest within whole-slide images. Results: Worked examples demonstrate that intratumor measurements such as apoptosis, cell proliferation, and immune cell population density can be quantitated in a spatially and drug concentration-dependent manner, establishing in vivo profiles of pharmacodynamics and pharmacokinetics in tumors. Conclusions: Spatial image analysis of tumor response along gradients of local drug release is achievable in high throughput. The major advantage of this approach is the use of spatially aware annotation tools to correlate drug gradients with drug effects in tumors in vivo.

A Rapid Fabrication Methodology for Payload Modules, Piloted for the Observation of Queen Honey Bees (Apis mellifera) in Microgravity

Abstract Microgravity experiment modules for living organisms have been instrumental to space research, yet their design remains complex and costly. As the private space sector enables more widely available payloads for researchers, it is increasingly necessary to design experimental modules innovatively so that they are proportionately accessible. To ease this bottleneck, we developed a rapid fabrication methodology for producing custom modules compatible with commercial payload slots. Our method creates a unified housing geometry, based on a given component layout, which is fabricated in a digital design and subtractive manufacturing process from a single lightweight foam material. This module design demonstrated a 25–50% reduction in chassis weight compared with existing models, and is extremely competitive in manufacturing time, simplicity, and cost. To demonstrate the ability to capture data on previously limited areas of space biology, we apply this methodology to create an autonomous, video-enabled module for sensing and observing queen and retinue bees aboard the Blue Origin New Shepard 11 (NS-11) suborbital flight. To explore whether spaceflight impacts queen fitness, results used high-definition visual data enabled by the module's compact build to analyze queen-worker regulation under microgravity stress (n = 2, with controls). Overall, this generalizable method for constructing experimental modules provides wider accessibility to space research and new data on honey bee behavior in microgravity.

1121. Implementation and Evaluation of a Virtual Microbiology Laboratory for Pharmacy Students

BackgroundHealth professions students learn microbiology concepts during in-person laboratories (labs). While highly rated by students, labs are extremely resource- and time-intensive. A virtual lab may minimize resource use while maintaining educational value. We report on the implementation and evaluation of a virtual lab designed to teach clinical microbiology to pharmacy students during an infectious diseases course.MethodsWe created a video in our clinical microbiology lab to depict the steps involved in processing and analyzing a patient sample. We also designed 2 web-based, interactive modules for students to practice lab techniques, such as virtually streaking an agar plate. Students viewed the video and completed the modules prior to attending a 2-hour in-person, case-based, small group discussion on higher-order clinical microbiology concepts. All students were invited to complete a post-session evaluation that assessed achievement of session objectives.ResultsSixty-nine students (65%) completed the survey. Students highly rated the video, modules, and in-class cases (Table 1). Fewer students felt confident explaining the clinical microbiology process, compared to selecting antibiotics, interpreting cultures, explaining Gram stains, and interpreting an antibiogram (Table 2). Student comments highlighted the value of the video, modules, and instructor facilitation during the in-class session. Students also suggested improvements with the module user interface and reinforcement of certain topics (e.g. clinical breakpoints) during the in-class session.Table 1: Student Ratings of the Quality of Instructional Materials Table 2: Student Self-Reported Agreement with Achievement of Session Objectives ConclusionWe demonstrated successful implementation a virtual microbiology lab within a pharmacy course. Overall student ratings of materials were favorable. We plan to refine and re-offer the virtual micro lab next year and measure its association with student performance. To facilitate the adaptation of this virtual lab by other schools, our teaching materials are available for use via https://vimeo.com/390087512 (video) and http://tiny.ucsf.edu/atlas (modules).Disclosures All Authors: No reported disclosures

User Preferences for Privacy Protection Methods in Mobile Health Apps: A Mixed-Methods Study.

Background:Mobile health (mHealth) apps have the potential to facilitate convenient health care delivery and self-management of health. However, many users have concerns about their privacy when they use mHealth apps. Different apps provide different solutions for protecting users' privacy.Objective:The purpose of this study was to determine user preferences among the several privacy protection methods used in current mHealth apps and the reasons behind their preferences.Methods:Five privacy protection methods currently used in mHealth apps were presented to a group of study participants who had mild or moderate depression and expressed concerns about privacy of information when they used mental health apps. After a demonstration of the methods, study participants were asked to fill out a questionnaire and indicate their perceived privacy protection level (PPPL) of each method, their preference rating for each method, and the privacy protection methods they had used in the past. A brief interview was then conducted to collect study participants' comments on these methods and elicit the reasons for their preference ratings. Statistical analysis was performed to determine the statistical significance of differences in participants' preference ratings and in the PPPLs obtained for the five methods. Study participants' comments on the privacy protection methods and suggestions were noted and summarized.Results:Forty (40) study participants were selected from a large candidate pool using the IRB approved selection criteria. All study participants viewed the app demonstration and understood the five privacy protection methods properly, which was indicated by their correct sorting of the PPPL of the five methods in their answers to the questionnaire. All study participants specified their preferences with respect to these methods and provided the rationale behind their selections on the questionnaire and during the brief interview. The results indicate that the users preferred privacy protection methods with customizable modules in multi-purpose apps because of their convenience and strong privacy protection, where the customization can be done either in the app or via a Web portal.Conclusions:This study identified user preferred privacy protection methods. These identified privacy protection methods may be used in many types of apps that perform sensitive health information management to better protect users' privacy and encourage more users to adopt these mHealth apps.

A Deep Learning Approach to Photoacoustic Wavefront Localization in Deep-Tissue Medium.

Optical photons undergo strong scattering when propagating beyond 1-mm deep inside biological tissue. Finding the origin of these diffused optical wavefronts is a challenging task. Breaking through the optical diffusion limit, photoacoustic (PA) imaging (PAI) provides high-resolution and label-free images of human vasculature with high contrast due to the optical absorption of hemoglobin. In real-time PAI, an ultrasound transducer array detects PA signals, and B-mode images are formed by delay-and-sum or frequency-domain beamforming. Fundamentally, the strength of a PA signal is proportional to the local optical fluence, which decreases with the increasing depth due to depth-dependent optical attenuation. This limits the visibility of deep-tissue vasculature or other light-absorbing PA targets. To address this practical challenge, an encoder-decoder convolutional neural network architecture was constructed with custom modules and trained to identify the origin of the PA wavefronts inside an optically scattering deep-tissue medium. A comprehensive ablation study provides strong evidence that each module improves the localization accuracy. The network was trained on model-based simulated PA signals produced by 16 240 blood-vessel targets subjected to both optical scattering and Gaussian noise. Test results on 4600 simulated and five experimental PA signals collected under various scattering conditions show that the network can localize the targets with a mean error less than 30 microns (standard deviation 20.9 microns) for targets below 40-mm imaging depth and 1.06 mm (standard deviation 2.68 mm) for targets at a depth between 40 and 60 mm. The proposed work has broad applications such as diffused optical wavefront shaping, circulating melanoma cell detection, and real-time vascular surgeries (e.g., deep-vein thrombosis).

OpenWorkstation: A modular open-source technology for automated in vitro workflows

Automation liberates scientific staff from repetitive tasks, decreases the probability of human error and consequently enhances the reproducibility of lab experiments. However, the use of laboratory automation in academic laboratories is limited due to high acquisition costs and the inability to customize off-the-shelf hardware. To address these challenges, we present an Open Source Hardware concept, referred to as OpenWorkstation, to build an assembly line-inspired platform consisting of ready-to-use and customizable modules. In contrast to current standalone solutions, the OpenWorkstation concept enables the combination of single hardware modules – each with a specific set of functionalities – to a modular workstation to provide a fully automated setup. The base setup consists of a pipetting and transport module and is designed to execute basic protocol steps for in vitro research applications, including pipetting operations for liquids and viscous substances and transportation of cell culture vessels between the modules. We demonstrate the successful application of this concept within a case study by the development of a storage module to facilitate high-throughput studies and a photo-crosslinker module to initiate photo-induced polymerization of hydrogel solutions. We present a Systems Engineering framework for customized module development, guidance for the design and assembly of the presented modules, and operational instructions on the usage of the workstation. By combining capabilities from various open source instrumentations into a modular technology platform, the OpenWorkstation concept will facilitate efficient and reliable experimentation for in vitro research. Ultimately, this concept will allow academic groups to improve replicability and reproducibility in cell culture process operations towards more economical and innovative research in the future.

LEGO-compatible modular mapping phantom for magnetic resonance imaging

Physical phantoms have been widely used for performance evaluation of magnetic resonance imaging (MRI). Although there are many kinds of physical phantoms, most MRI phantoms use fixed configurations with specific sizes that may fit one or a few different types of radio frequency (RF) coils. Therefore, it has limitations for various image quality assessments of scanning areas. In this article, we report a novel design for a truly customizable MRI phantom called the LEGO-compatible Modular Mapping (MOMA) phantom, which not only serves as a general quality assurance phantom for a wide range of RF coils, but also a flexible calibration phantom for quantitative imaging. The MOMA phantom has a modular architecture which includes individual assessment functionality of the modules and LEGO-type assembly compatibility. We demonstrated the feasibility of the MOMA phantom for quantitative evaluation of image quality using customized module assembly compatible with head, breast, spine, knee, and body coil features. This unique approach allows comprehensive image quality evaluation with wide versatility. In addition, we provide detailed MOMA phantom development and imaging characteristics of the modules.

Laboratory module design for Biology Students: A Systematic review

Module design for students’ laboratory activities plays an important role in the effective implementation of scientific investigation in the laboratory. The purpose of this review is to examine the types, topics, competencies, and approaches to develop laboratory module for biology students. The review of the literature was conducted systematically. Eighteen research articles were selected from 41 articles published within 2009 and 2019. The systematic review followed 5 steps. The research articles were searched using Google Scholar's online database and then traced back from the relevant international and national journals. The articles collected were selected by two reviewers who rated the quality. The results of the analysis showed that the laboratory modules are designed using the following basis: online, research, quantitative skills, inquiry, and traditional. The biology topics focused are Genetics, Ecology, Phylogenetics, Biochemistry, Molecular Biology, Evolution, Biotechnology, and Tissue Culture. The methods used for laboratory module development by Indonesian researchers are 4D, ADDIE, R & D, Dick & Carey, and Borg & Gall, while international researchers generally do not specify the name of the method used. Generally, the need analysis which focuses on the novelty of the developed concept is conducted in the beginning. It continues with module designing, validation, implementation, and response survey from the students as the module users.

Implementation of an Open-Source Electronic Health Record for Decision-Support Education in Medical Informatics.

Access to electronic medical record systems is limited in many medical informatics education programs. The objective of this study was to inventory open-source patient record systems with decision support capabilities, implement a system for educational use, and test the effect of the system on students' learning. We sought systems that were under active development, with source code available, having an SQL-queryable database, and having decision support capabilities. We identified 20 candidate electronic health record systems, of which 6 mentioned decision support capabilities in their documentation. Of these, the OpenMRS system appeared to meet all of the requirements for use in our course; however, decision support capabilities needed to be added by use of a custom module implementing Arden2Bytecode, an Arden Syntax interpreter. Students who used this system showed an improvement in their knowledge of decision support systems and their capabilities. We conclude that there are a number of promising open-source electronic patient record systems currently under active development, but decision support capabilities are still immature. We anticipate further developments in this area in the coming years.

A top-down approach to estimate global RO desalination water production considering uncertainty

Desalination is one of the promising methods to address the water shortage, especially for the coastal areas. To understand the present status of the desalination industry, it is of importance to accurately estimate the magnitude of water production of the desalination industry. However, traditional bottom-up approaches to estimate desalination water production magnitude are often relying on data of individual water treatment plants and may lead to contradictory results since it is extremely difficult to obtain accurate desalination water production data of most water treatment plants. Considering RO modules are manufactured by limited major suppliers globally, we propose a top-down approach to estimate global RO desalination water production. The approach is to estimate RO desalination water production based on the quantity of RO modules sold globally by the RO module manufacturers. This provides an obvious advantage as there are much less RO module manufacturers than the RO module users (water treatment plants). Using this approach and the most recently available RO module sales data, the global water production of RO desalination in 2017 is 122.0 ± 31.5 million m3/d (mean ± SD, at the 95% confidence interval), which is 53.2 million m3/d higher than that of the International Desalination Association estimate (compared by the mean).

Multi-modal Anterior Eye Imager Combining Ultra-High Resolution OCT and Microvascular Imaging for Structural and Functional Evaluation of the Human Eye

To establish complementary information for the diagnosis and evaluation of ocular surface diseases, we developed a multi-modal, non-invasive optical imaging platform by combining ultra-high resolution optical coherence tomography (UHR-OCT) with a microvascular imaging system based on slit-lamp biomicroscopy. Our customized UHR-OCT module achieves an axial resolution of ≈2.9 μm in corneal tissue with a broadband light source and an A-line acquisition rate of 24 kHz with a line array CCD camera. The microvascular imaging module has a lateral resolution of 3.5 μm under maximum magnification of ≈187.5× with an imaging rate of 60 frames/s, which is sufficient to image the conjunctival vessel network and record the movement trajectory of clusters of red blood cells. By combining the imaging optical paths of different modules, our customized multi-modal anterior eye imaging platform is capable of performing real-time cross-sectional UHR-OCT imaging of the anterior eye, conjunctival vessel network imaging, high-resolution conjunctival blood flow videography, fluorescein staining and traditional slit-lamp imaging on a single device. With self-developed software, a conjunctival vessel network image and blood flow videography were further analyzed to acquire quantitative morphological and hemodynamics parameters, including vessel fractal dimensions, blood flow velocity and vessel diameters. The ability of our multi-modal anterior eye imager to provide both structural and functional information for ophthalmic clinical applications was demonstrated on a healthy human subject and a keratitis patient.