Name: Determination of Dose Threshold Using the Machine-Vision Synchronization (MVS) and Dose Software
Uploaded: 2023-06-23T14:25:00
Duration: 2 min 12 s
Description: Watch this Scientific Journal Video about Determination of Dose Threshold Using the Machine-Vision Synchronization MVS and Dose Software at JoVE.com

determination of dose threshold using the machine-vision synchronization (mvs) and dose software

머신 비전 접근 방식을 사용한 TEM 워크플로우, 결과 분석 및 데이터 관리

Transmission electron microscopes (TEMs) and their capabilities have benefited enormously from advances in cameras, detectors, sample holders, and computing technologies. However, these advances are hampered by disconnected data streams, limitations of human operation, and cumbersome data analysis1,2. Moreover, in situ and operando experiments adapt TEMs into real-time nanoscale laboratories, enabling samples to be studied in gas or liquid environments while simultaneously applying a range of external stimuli3,4,5. The adoption of such complex workflows have only magnified these limitations, and the resulting increase of the size and complexity of these data streams is an area of growing concern. Thus, there is a growing emphasis on utilizing machine-actionability to find, access, interoperate, and reuse data, a practice known as the FAIR principles6. Publishing research data in accordance with the FAIR principles concept has received favorable attention from governmental agencies around the world7,8, and application of the FAIR principles using machine-vision software is a key step in their adoption.
A machine-vision synchronization (MVS) software platform has been developed in response to the specific pain points inherent to performing and analyzing complex, metadata-heavy TEM experiments (particularly in situ and operando experiments)9. Once installed on the TEM, the MVS software connects, integrates, and communicates with the microscope column, detectors, and integrated in situ systems. This enables it to continuously collect images and align those images with their experimental metadata, forming a comprehensive searchable database, a timeline of the experiment from start to finish (Figure 1). This connectivity allows the MVS software to apply algorithms that intelligently track and stabilize a region of interest (ROI), even when samples are undergoing morphological changes. The software applies adjustments to stage, beam, and digital corrections as necessary to stabilize the ROI through its Drift Control and Focus Assist functions. In addition to enriching the images with the raw metadata produced from the different experimental systems, the software can produce new, computational metadata using image analysis algorithms to calculate variables between images, which allow it to automatically correct for sample drift or changes in focus.
TEM images, and their associated metadata collected through the MVS software, are organized as an experimental timeline which can be opened and viewed by anyone via the free, offline version of the analysis software, Studio (hereafter referred to as the analysis software)10. During an experiment, the MVS software syncs and records three types of images from the microscope&#39;s camera or detector, which are displayed at the top of the timeline below the image viewer: single acquisition (individual single aquisition images acquired directly from the TEM software), raw&#160;(images from the detector/camera live stream that have not had any digital drift corrections applied; these images may have been physically corrected via stage movement or beam shift), and drift corrected (images from the detector/camera live stream that have been digitally drift). Data collected during an experiment or session can be further refined into smaller sections or snippets of data, known as collections, with no loss of embedded metadata. From the analysis software, images, image stacks, and metadata can be directly exported into a variety of open format images and spreadsheet types for analysis using other tools and programs.
The framework of microscope control, stabilization, and metadata integration enabled by the MVS software also allows the implementation of additional machine-vision programs or modules, designed to alleviate limitations in current TEM workflows. One of the first modules developed to take advantage of this synchronization platform is electron dose calibration and spatial tracking of beam exposed areas within the sample. All TEM images are formed from the interaction between the sample and the electron beam. However, these interactions can also result in negative, inescapable impacts on the sample, such as radiolysis and knock-on damage11,12, and require a careful balance between applying a high enough electron dose to generate the image and minimizing the resulting beam damage13,14.
Although many users rely on screen current measurements to estimate the electron dose, this method has been shown to widely underestimate the actual beam current15. Qualitative dose values can be obtained via the screen current on the same microscope with the same settings, but reproducing these dose conditions using different microscopes or settings is highly subjective. Additionally, any imaging parameter adjustments made by the user during the experiment, such as spot size, aperture, magnification, or intensity, require a separate measurement of the screen current to calculate the resulting dose. Users must either rigorously limit the imaging conditions used during a given experiment or meticulously measure and record each lens condition used, significantly complicating and extending the experiment beyond what is feasible for normal operation of the microscope16,17.
Dose, referred to as dose software for this protocol, is a dose calibration software module that utilizes a dedicated calibration holder designed to enable automated current measurements. A Faraday cup, the gold standard for accurate beam current calibration15, is integrated into the tip of the calibration holder. The MVS software performs a series of beam current and beam area calibrations for each lens condition and embeds those values on the images at the pixel level.
In this video article, MVS software protocols designed to enhance all areas of the TEM workflow are presented using representative nanomaterial samples. A beam sensitive zeolite nanoparticle sample14 is used to demonstrate the calibration and dose management workflows. We perform a representative in situ heating experiment using an Au/FeOx nanocatalyst18,19 sample that undergoes significant morphological changes when heated. This in situ experiment highlights the software&#39;s stabilization algorithms and its ability to collate multiple streams of metadata, which is an inherent challenge for in situ and operando studies. Although not described in the protocol, because of its unique electron dose sensitivity, we discuss representative examples of the software&#39;s utility for liquid-EM studies (protocols for which have been previously reported in the literature20,21,22), and how these techniques can be applied to improve the understanding of the effect of dose on liquid-EM experiments. Finally, we show how data analysis is streamlined using the offline analysis software to visualize, filter, and export a variety of image, video, and data files into other accessible formats.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/65446/65446fig01.jpg" /> 
Figure 1: User interface examples for MVS and analysis software. (A) The synchronization software image viewing pane and control panel. A connection between the TEM and the synchronization software is established by activating the Connect button, which streams the images and metadata from the microscope into the synchronization software. From the image viewer, the operator can perform a variety of machine-vision assisted operations, such as Drift Correct and Focus Assist. It also provides the ability to apply Tag Images and Review Session without disrupting data collection. (B) Screenshot of the image analysis software highlighting the location of the Image View Port, Timeline, and the Metadata and Analysis panel. The analysis software can be accessed at any point during an experiment to review the images acquired up to that time point using the Review Session button. <a href="https://www.jove.com/files/ftp_upload/65446/65446fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

저자 스포트라이트: 투과 전자 현미경 워크플로우, 결과 분석 및 데이터 관리에 대한 머신 비전 접근 방식  

투과 전자 현미경 워크플로우, 결과 분석 및 데이터 관리에 대한 머신 비전 접근 방식

This technology was developed to make high-performance TEM studies accessible to users of all skill levels. Furthermore, scientific advancements require the collaborative efforts of multiple investigators, so an efficient platform to share and analyze large, complex data sets is essential for successful research Operando and in situ studies transform a TEM into a real-time nanolaboratory, allowing researchers to explore the dynamic nano-scale processes that control materials'growth properties. One of the greatest challenges for in-situ TEM studies is isolating the beam irradiation effects from the intrinsic behavior of the sample.Accurate electron dose measurement and tracking is essential, but without dose management software, one can only measure electron dose rate rather than the total or critical dose Complex TEM workflows generate large data sets which must be manually aligned and indexed to their respective images. In this time-consuming process, the key information, such as adjustments to imaging conditions or samples environment, may be lost, complicating analysis and reproducibility. We have developed a machine-vision workflow to collect and index the images and metadata produced during an experiment into a data-enriched, searchable timeline.Computational and image analysis algorithms can calculate variables between images, apply corrections, and identify hidden trends. By calculating, synchronizing, and indexing new metadata into each image, multimodal analysis is suddenly a new possibility. For example, accurate accumulated dose and dose rate information in the zeolite images allows quantitative assessment of sample damage across thousands of images.We will continue to push the capabilities of in-situ TEM by making results accessible and interpretable and improving experimental reproducibility. This software is a platform to develop workflow-driven modules that target specific, historically difficult applications to make in-situ TEM experiments easier and more information rich.

Watch this Scientific Journal Video about Determination of Dose Threshold Using the Machine-Vision Synchronization MVS and Dose Software at JoVE.com

Determination of Dose Threshold Using the Machine-Vision Synchronization (MVS) and Dose Software  

Machine-Vision Synchronization(MVS) 및 Dose 소프트웨어를 사용한 선량 역치 결정

TEM 기기에서 MVS 소프트웨어 응용 프로그램을 열고 기타를 선택하여 시작합니다. 현미경을 MVS 소프트웨어에 연결합니다. 이미지 메타데이터 탭으로 이동하여 배율, 최대 선량 및 선량률을 선택하여 라이브 디스플레이에 표시되는 이미지 스트림에 오버레이합니다.사용자가 원하는 경우 다른 메타데이터가 포함될 수 있다. 복용량 탭을 엽니다. 선량 관리를 선택하고 선량 모니터링을 활성화합니다.그런 다음 선량 레이어 표시 및 위치 불확도 표시를 선택하여 자동 전자 선량 추적을 활성화하고 선량 색상 오버레이를 표시합니다. 저장을 누르기 전에 낮은 용량 수준과 높은 용량 수준에 대한 값을 설정합니다. 그런 다음 설정 탭으로 이동합니다.선량을 선택하고 선량 탐색 맵 불투명도 및 선량 이미지 오버레이 불투명도 값을 설정합니다. 라이브 이미지 뷰어 창에서 드리프트 보정(drift correct)을 클릭하여 드리프트 보정을 활성화합니다. 그런 다음 데이터 보기 탭으로 이동하여 메타데이터 값 디포커스 및 포커스 지수를 y축에 플로팅합니다.초점 지원을 활성화한 다음 초점 보정을 선택하여 자동 초점 지원의 보정을 실행합니다. 초점 보정 루틴이 완료되면 데이터 보기 탭을 닫습니다. MVS 소프트웨어에서 이미지 분석 탭을 열고 라이브 FFT 및 사분면 1 및 2 옵션을 활성화합니다.현미경 소프트웨어 컨트롤을 사용하여 전자 플럭스가 초당 약 600옹스트롬 제곱이 되도록 빔 조건을 조정합니다. 샘플의 새 영역으로 이동하고 MVS 소프트웨어의 라이브 뷰에서 샘플 ROI를 중앙에 배치합니다. 원자 구조와 FFT에 해당하는 스폿이 사라질 때까지 동일한 ROI를 지속적으로 이미징하면서 일정한 선량률을 유지합니다.

Research

JoVE Journal

Biology

Determination of Dose Threshold Using the Machine-Vision Synchronization (MVS) and Dose Software

A Machine-Vision Approach to Transmission Electron Microscopy Workflows, Results Analysis and Data Management

Transmission electron microscopy (TEM) enables users to study materials at their fundamental, atomic scale. Complex experiments routinely generate ...

연구

생물학

Dose Calibration of the Transmission Electron Microscope for TEM and Scanning TEM (STEM) Imaging Modes Using a Machine-Vision Approach

머신 비전 접근법을 사용한 TEM 및 주사 TEM(STEM) 이미징 모드를 위한 투과 전자 현미경의 선량 보정

Metadata and Trend Analysis and Data Export Using the Analysis Software

분석 소프트웨어를 사용한 메타데이터 및 추세 분석 및 데이터 내보내기

In Situ Heating Study of Gold on Iron Oxide Nanoparticles

산화철 나노 입자에 대한 금의 현장 가열 연구