Dataset Information

Large-scale analysis of high-speed atomic force microscopy data sets using adaptive image processing.

ABSTRACT: Modern high-speed atomic force microscopes generate significant quantities of data in a short amount of time. Each image in the sequence has to be processed quickly and accurately in order to obtain a true representation of the sample and its changes over time. This paper presents an automated, adaptive algorithm for the required processing of AFM images. The algorithm adaptively corrects for both common one-dimensional distortions as well as the most common two-dimensional distortions. This method uses an iterative thresholded processing algorithm for rapid and accurate separation of background and surface topography. This separation prevents artificial bias from topographic features and ensures the best possible coherence between the different images in a sequence. This method is equally applicable to all channels of AFM data, and can process images in seconds.

SUBMITTER: Erickson BW

PROVIDER: S-EPMC3512124 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Large-scale analysis of high-speed atomic force microscopy data sets using adaptive image processing.

Erickson Blake W BW Coquoz Séverine S Adams Jonathan D JD Burns Daniel J DJ Fantner Georg E GE

Beilstein journal of nanotechnology 20121113

Modern high-speed atomic force microscopes generate significant quantities of data in a short amount of time. Each image in the sequence has to be processed quickly and accurately in order to obtain a true representation of the sample and its changes over time. This paper presents an automated, adaptive algorithm for the required processing of AFM images. The algorithm adaptively corrects for both common one-dimensional distortions as well as the most common two-dimensional distortions. This met ...[more]

PMID: 23213638

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Project description:High-speed atomic force microscopy (HS-AFM) is a powerful tool for visualizing the dynamics of individual biomolecules. However, in single-molecule HS-AFM imaging applications, x,y-scanner ranges are typically restricted to a few hundred nanometers, preventing overview observation of larger molecular assemblies, such as 2-dimensional protein crystal growth or fibrillar aggregation. Previous advances in scanner design using mechanical amplification of the piezo-driven x,y-positioning system have extended the size of HS-AFM image frames to several tens of micrometer, but these large scanners may suffer from mechanical instabilities at high scan speeds and only record images with limited pixel numbers and comparatively low lateral resolutions (> 20-100 nm/pixel), complicating single-molecule analysis. Thus, AFM systems able to image large sample areas at high speeds and with nanometer resolution have still been missing. Here, we describe a HS-AFM sample-scanner system able to record large topographic images (≤ 36 × 36 µm2) containing up to 16 megapixels, providing molecular resolution throughout the image frame. Despite its large size, the flexure-based scanner features a high resonance frequency (> 2 kHz) and delivers stable operation even at high scans speeds of up to 7.2 mm/s, minimizing the time required for recording megapixel scans. We furthermore demonstrate that operating this high-speed scanner in time-lapse mode can simultaneously identify areas of spontaneous 2-dimensional Annexin A5 crystal growth, resolve the angular orientation of large crystalline domains, and even detect rare crystal lattice defects, all without changing scan frame size or resolution. Dynamic processes first identified from overview scans can then be further imaged at increased frame rates in reduced scan areas after switching to conventional HS-AFM scanning. The added ability to collect large-area, high-resolution images of complex samples within biological-relevant time frames extends the capabilities of HS-AFM from single-molecule imaging to the study of large dynamic molecular arrays. Moreover, large-area HS-AFM scanning can generate detailed structural data sets from a single scan, aiding the quantitative analysis of structurally heterogenous samples, including cellular surfaces.

Dataset Information

Large-scale analysis of high-speed atomic force microscopy data sets using adaptive image processing.

Publications

Large-scale analysis of high-speed atomic force microscopy data sets using adaptive image processing.

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