Image Processing Software Package Research Articles

Step height measurement of monoatomic silicon crystal lattice steps with a commercial atomic force microscope

Abstract Precise control of advanced materials relies on accurate dimensional metrology at the sub-nanometre scale. At this scale, the accuracy of scanning probe microscopy (SPM) has been limited by the lack of traceable transfer standard artefacts with calibration structures of suitable dimensions. With the adoption in 2019 of the silicon crystal lattice spacing as a secondary realization of the metre in the International System of Units (SI), SPM users have direct access to a realization of the SI metre at the sub-nanometre level by means of the step height of self-assembled monatomic lattice steps that can form on the surface of silicon crystals. A key challenge of successfully adopting this pathway is establishing the need for established protocols to minimize measurement errors and artifacts in routine laboratory use.
In this study, step height measurements of monoatomic lattice steps in an ordinal/staircase structure on a Si(111) crystal surface have been derived from images acquired with a commercially available, research-level atomic force microscope (AFM). Measurement results derived from AFM images using three different SPM image processing and analysis software packages are compared. Significant sources of measurement uncertainty are identified; principally the contribution from the dependence on scan direction. The calibration of the
AFM derived from this measurment was used to traceably measure the sub-nanometre lattice steps on a silicon carbide crystal surface to demonstrate the viability of this calibration pathway.

Planetary orbital mapping and mosaicking (POMM) integrated open source software environment

Several Open Source planetary orbital mapping and utility image processing software packages, including, VICAR, AFIDS, ISIS, GDAL, and GeoTIFF, have been integrated into a single software environment (POMM), where package programs can be run independently from a Linux command line, or combined in synergistic scripts that facilitate advanced trans-package applications. Several integrated scripts have been prepared to simplify some of the more difficult database building tasks such as (1) image co-registration (for stacking and time series analysis), (2) mosaicking (for regional analysis), and (3) map-projection of raw Planetary Data System (PDS) images for selected Mars and Luna sensor systems. A user interface/GUI is provided for the three planetary applications, but the underlying scripts can also be modified by an advanced user and run at the command-line. POMM is Open Source software available in “docker” container and “Yum-Install” versions that support cross-platform installation on Windows, Apple, and Linux products using available desktop applications and/or virtual containers. However, installation on systems requiring emulation can be slow, and the installation process can be challenging.

KairoSight-3.0: A validated optical mapping software to characterize cardiac electrophysiology, excitation-contraction coupling, and alternans.

Cardiac optical mapping is an imaging technique that measures fluorescent signals across a cardiac preparation. Dual optical imaging of voltage-sensitive and calcium-sensitive probes allows for simultaneous recordings of cardiac action potentials and intracellular calcium transients with high spatiotemporal resolution. The analysis of these complex optical datasets is both time intensive and technically challenging; as such, we have developed a software package for semi-automated image processing and analysis. Herein, we report an updated version of our software package (KairoSight-3.0) with features to enhance the characterization of cardiac parameters using optical signals. To test software validity and applicability, we used Langendorff-perfused heart preparations to record transmembrane voltage and intracellular calcium signals from the epicardial surface. Isolated hearts from guinea pigs and rats were loaded with a potentiometric dye (RH237) and/or calcium indicator dye (Rhod-2AM) and fluorescent signals were acquired. We used Python 3.8.5 programming language to develop the KairoSight-3.0 software. Cardiac maps were validated with a user-specified manual mapping approach. Manual maps of action potential duration (30 or 80 % repolarization), calcium transient duration (30 or 80 % reuptake), action potential and calcium transient alternans were constituted to validate the accuracy of software-generated maps. Manual and software maps had high accuracy, with >97 % of manual and software values falling within 10 ms of each other and >75 % within 5 ms for action potential duration and calcium transient duration measurements (n = 1000-2000 pixels). Further, our software package includes additional measurement tools to analyze signal-to-noise ratio, conduction velocity, action potential and calcium transient alternans, and action potential-calcium transient coupling time to produce physiologically meaningful optical maps. KairoSight-3.0 has enhanced capabilities to perform measurements of cardiac electrophysiology, calcium handling, alternans, and the excitation-contraction coupling with satisfactory accuracy.

Application of a hyperspectral camera for colorimetric measurements on polychrome surfaces in a controlled environment and evaluation of three image processing software for displaying colorimetric data: Pros and cons of the methodology presented

AbstractThis work explores the potential of a compact hyperspectral camera, Specim IQ, for the remote colorimetric study of polychrome surfaces in controlled environments. These measurements are generally made with dedicated instruments, such as colorimeters or spectrophotometers, which require contact with the surface and coverage areas of the order of 10s of mm2. These two characteristics, contact and a very small analysis area, can severely limit the study of polychrome surfaces, since the measured areas are not necessarily representative of the entire surface. In addition, it is not always possible to touch the objects being analyzed. A possible alternative is the use of compact hyperspectral cameras, such as Specim IQ, for the in situ study of the spectral and colorimetric characteristics of these surfaces. To better address this research, which is still in the preliminary phase, a 2 × 45°/0° geometry measuringement was used. The illumination of the image plane at 45° with respect to the camera made it possible to eliminate the components reflected specularly on the camera lens. With this shooting geometry, Labsphere Color and Gray Reflectance Standards (eight color and four gray standards) were analyzed and placed on seven different color backgrounds. With the spectral data acquired, it was possible to calculate the color of the targets and display the colorimetric values by means of three commonly used image processing software packages. In this way, it was possible to define for this hyperspectral camera a measurement‐data processing procedure applicable to measurements in the laboratory aimed at studying the color of polychrome surfaces.

Hoku—A Multispectral Software Tool to Recover Erased Writing on Palimpsests

Abstract An image processing software package called Hoku is available to the public, free-of-charge, for use in recovering erased text from multispectral images of palimpsests. This software was developed by the author for his own use in recovering text, but has been built with an intuitive user interface that makes it suitable for non-technical users. It is written in Java and runs on both Windows and macOS computers. In this article, examples will be given of Hoku image processing results on data sets from three imaging systems—MegaVision, Phase One, and Lumiere Technology.

Histogram equalization using a selective filter

AbstractMany popular modern image processing software packages implement a naïve form of histogram equalization. This implementation is known to produce histograms that are not truly uniform. While exact histogram equalization techniques exist, these may produce undesirable artifacts in some scenarios. In this paper we consider the link between the established continuous theory for global histogram equalization and its discrete implementation, and we formulate a novel histogram equalization technique that builds upon and considerably improves the naïve approach. We show that we can linearly interpolate the cumulative distribution of a low-bit image by approximately dequantizing its intensities using a selective box filter. This helps to distribute the intensities more evenly. The proposed algorithm is subsequently evaluated and compared with existing works in the literature. We find that the method is capable of producing an equalized histogram that has a high entropy, while distances between similar intensities are preserved. The described approach has implications on several related image processing problems, e.g., edge detection.

ContinuousFlex: Software package for analyzing continuous conformational variability of macromolecules in cryo electron microscopy and tomography data

ContinuousFlex is a user-friendly open-source software package for analyzing continuous conformational variability of macromolecules in cryo electron microscopy (cryo-EM) and cryo electron tomography (cryo-ET) data. In 2019, ContinuousFlex became available as a plugin for Scipion, an image processing software package extensively used in the cryo-EM field. Currently, ContinuousFlex contains software for running (1) recently published methods HEMNMA-3D, TomoFlow, and NMMD; (2) earlier published methods HEMNMA and StructMap; and (3) methods for simulating cryo-EM and cryo-ET data with conformational variability and methods for data preprocessing. It also includes external software for molecular dynamics simulation (GENESIS) and normal mode analysis (ElNemo), used in some of the mentioned methods. The HEMNMA software has been presented in the past, but not the software of other methods. Besides, ContinuousFlex currently also offers a deep learning extension of HEMNMA, named DeepHEMNMA. In this article, we review these methods in the context of the ContinuousFlex package, developed to facilitate their use by the community.

MiTiSegmenter: Software for high throughput segmentation and meshing of microCT data in microtiter plate arrays

Lab-based microCT is a powerful means of visualising the internal structure of physical specimens deployed across the physical sciences, engineering and the arts. As its popularity has grown, demand for bulk digitisation of multiple samples within a single scan has increased. High throughput workflows can increase sample sizes and reduce scan time, yet downstream segmentation and meshing remain a bottleneck. We present MiTiSegmenter as a new tool for the bulk archiving of valuable zooarchaeological and palaeontological remains. We foresee MiTiSegmenter as particularly useful when incorporated into workflows that ultimately require the destructive testing of specimens, including sampling for ancient DNA and proteomics. The software may also play an important role in national museums' ongoing mass digitisation efforts, facilitating the high-speed archiving of specimen 3D morphology across extensive collections with very minimal user intervention or prior training. •We present MiTiSegmenter, a software package for semi-automated image processing and segmentation of array-based batch microCT data.•Implemented in Python, MiTiSegmenter expedites cropping, meshing and exporting samples within stacked microtiter plates, facilitating the rapid digitisation of hundreds-thousands of samples per scan.•We illustrate MiTiSegmenter's capabilities when applied to bulk archiving of valuable zooarchaeological and palaeontological remains

Standardized analysis of juvenile pyroclasts in comparative studies of primary magma fragmentation: 2. Choice of size fraction and method optimization for particle cross-sections

The morphological and textural features of juvenile pyroclasts record crucial details on magma conditions at the time of fragmentation. Their study is therefore essential to better understand the dynamics of explosive eruptions. Unfortunately, the absence of a standardized protocol of investigation hinders data reproducibility and comparison among different laboratories. Here we focus on morphometric parameters, 2D crystallinity and 2D vesicularity resulting from cross-section analysis of juvenile particles using backscattered electron imaging, and address the following questions: (i) how to prepare polished epoxy grain mounts, (ii) which pixel density to be used, (iii) how to facilitate image preparation and image analysis, (iv) which sample size is necessary to obtain statistically robust results, and (v) what is the optimum size fraction for analysis. We test juvenile particles in grain size bins ranging from 2–1 mm (− 1 to 0ɸ) to 88–63 µm (+ 3.5 to + 4ɸ), using samples from the 1977 Ukinrek eruption. We find that the required resolution ranges from 75 000 to 10 000 pixels per particle, depending on the size fraction, higher than previously postulated. In the same size ranges, less than 50 grains per size fraction and sample are needed to get robust averages. Based on theoretical, empirical, and practical considerations, we propose 0.71–0.5 mm (+ 0.5 to + 1ɸ) as the optimum size fraction to be analyzed as particle cross-sections in standardized comparative studies of magma fragmentation. We provide a detailed guide for preparing polished epoxy grain mounts and introduce a software package (PASTA) for semi-automated image preparation, image processing, and measurement of morphological and textural parameters.

Application of Google earth engine python API and NAIP imagery for land use and land cover classification: A case study in Florida, USA

The analysis of land use and land cover data provides invaluable support to a variety of land management and conservation activities. However, historically its application has been limited by high costs associated with data acquisition, analysis, and classification. In recent years, freely available satellite imagery and geospatial data sets and rapid advancement in data analysis capabilities provide immense opportunities to understand and solve the real-world environmental problems. Open-source platforms such as Google Earth Engine (GEE) provide a planetary-scale environmental science data and analyses capability at much greater efficiency and accuracy than the traditional workflows. We evaluated the GEE Python API utility for classifying the freely available NAIP aerial imagery of 2017 to derive the land use land cover (LULC) information of a Panhandle area of Florida, USA. We identified eight major LULC classes with an overall accuracy of 86% and Kappa value of 79%. We completed all remote sensing data analyses procedures including data retrieval, classification, and report preparation in the Jupyter notebook, an open-source web application. Computation time for the procedure was less than 15 min. Our results demonstrate the usefulness of this approach for conducting land use and land cover analysis using much less time, money, and human resources. The open-source nature of GEE Python API and its library of remote sensing data could benefit remote sensing projects throughout the world, especially where access to commercial image processing software packages and remote sensing data are limited.

Phone App to Perform Quality Control of Pesticide Spray Applications in Field Crops

It has been recognized for decades that low and inconsistent spray coverages of pesticide applications represent a major challenge to successful and sustainable crop protection. Deployment of water-sensitive spray cards combined with image analysis can provide valuable and quantitative insight into spray coverage. Herein we provide description of a novel and freely available smartphone app, “Smart Spray”, for both iOS and Android smart devices (iOS and Google app stores). More specifically, we provide a theoretical description of spray coverage, and we describe how Smart Spray and similar image-processing software packages can be used as decision support tools and quality control for pesticide spray applications. Performance assessment of the underlying pixel classification algorithm is presented, and we detail practical recommendations on how to use Smart Spray to maximize accuracy and consistency of spray coverage predictions. Smart Spray was developed as part of ongoing efforts to: (1) maximize the performance of pesticide sprays, (2) minimize pest-induced yield loss and to potentially reduce the amount of pesticide used, (2) reduce the risk of target pests developing pesticide resistance, (3) reduce the risk of spray drift, and (4) optimize spray application costs by introducing a quality control.

Automated Nanoparticle Analysis in Surface Plasmon Resonance Microscopy.

The unique capability of surface plasmon resonance microscopy (SPRM) in single nanoparticle analysis has found use in various chemical and biological applications. While SPRM offers exceptional sensitivity, the statistical analysis of numerous nanoparticles has been extremely laborious and time-consuming. Herein, we presented an image processing software package for nanoparticle analysis in SPRM, which is empowered by a deep learning algorithm. This package enabled fully automated nanoparticle identification, digital counting, three-dimensional tracking of particle locations, and quantification of dwell time and Brownian motion properties. With a built-in image filtering process to improve the contrast, robust identification and analysis have been achieved from SPRM images of low refractive index nanoparticles. This software tool would largely promote the translation of SPRM technology into the digital sensing platform for high throughput sample screening.

The Use of Image Processing and Analysis in Automated Biological Dosimetry

Biological dosimetry based on cytogenetic markers such as dicentric chromosome (DC) and micronuclei (MN) is, until now, the most frequently used method to estimate the radiation dose in the radiological accident event. Another biomarker that recently gains popularity in biodosimetry is γH2AX. All these three assays are microscope-based biodosimetry techniques, and therefore need manual scoring to estimate the radiation dose. Unfortunately, the manual scoring of these assays is time-consuming and labor-intensive. In the case of a large-scale radiological accident when many people are exposed to radiation, it is very useful to use image processing and analysis in the scoring process to obtain a faster result. Several commercial systems or open-source image processing software packages already developed automated scoring of DC, MN, and γH2AX assays. This article describes how image processing and analysis were applied in automated biodosimetry based on the DC, MN, and γH2AX assays.

PySAP: Python Sparse Data Analysis Package for multidisciplinary image processing

We present the open-source image processing software package PySAP (Python Sparse data Analysis Package) developed for the COmpressed Sensing for Magnetic resonance Imaging and Cosmology (COSMIC) project. This package provides a set of flexible tools that can be applied to a variety of compressed sensing and image reconstruction problems in various research domains. In particular, PySAP offers fast wavelet transforms and a range of integrated optimisation algorithms. In this paper we present the features available in PySAP and provide practical demonstrations on astrophysical and magnetic resonance imaging data.

Программно-методический комплекс обработки изображений при проведении лётных испытаний иконических оптико-электронных систем

The authors present a method for determining the modulation transfer function of iconic opticand-electronic systems for remote sensing the Earth, developed to assess their quality during flight tests and propose a specialized digital image processing software package that implements an algorithm for determining the modulation transfer function. The adequacy of the developed method and the functioning of a specialized software complex for processing digital images is confirmed by satisfactory convergence of the analytical system and the aviation multi-functional optical-electronic one derived from the flight testing the functions of the modulation transfer. The features of mathematical modeling iconic optical-electronic systems of the Earth remote sensing during the tests are presented. The authors present the structure of the mathematical model of iconic optoelectronic systems, which reflects the main links that affect the quality of the image formed. The main quality criteria used in practice for evaluating iconic optical-electronic systems using the mathematical model are presented.

Relationship between local microstructure and superconducting properties of commercial YBa2Cu3O7−δ bulk

The relationship between local microstructure and superconducting properties of commercially prepared YBa2Cu3O7−δ single-grain bulk superconductor was investigated. The small samples for magnetization measurements were taken from the beginning and end of the a-growth sector and the c-growth sector as well as from the beginning and end of a/a-growth sector boundary. The field dependence of the magnetic moment was measured at temperatures starting from liquid helium (4.2 K) to liquid nitrogen (77 K) using the commercial Magnetic Property Measurement System with a magnetic field of up to 7 and 18 T. The microstructure was analysed using polarised light optical microscopy and scanning electron microscopy. The quantitative microstructural data were determined using an image processing software package. Microstructure analysis was focused on the size and volume fraction of Y2BaCuO5 particles as well as on the characterisation of subgrain structure. These measurements showed that not only inhomogeneous distribution of Y2BaCuO5 particles had influence on the critical current density but it can also be significantly affected by the subgrain structure within the bulk or by local contamination of YBa2Cu3O7−δ from the seed during fabrication process. It was observed that the critical current density along the a/a-growth sector boundary could be substantially higher in comparison to the other parts of the bulk and this behaviour can be related to the subgrain structure in the sample.

Open source bioimage informatics tools for the analysis of DNA damage and associated biomarkers

DNA double-strand breaks (DSBs) are critical cellular lesions that represent a high risk for genetic instability. DSBs initiate repair mechanisms by recruiting sensor proteins and mediators. DSB biomarkers, like phosphorylated histone 2AX (γH2AX) and p53-binding protein 1 (53BP1), are detectable by immunofluorescence as either foci or distinct patterns in the vicinity of DSBs. The correlation between the number of foci and the number of DSBs makes them a useful tool for quantification of DNA damage in precision medicine, forensics and cancer research. The quantification and characterization of foci ideally uses large cell numbers to achieve statistical validity. This requires software tools that are suitable for the analysis of large complex data sets, even for users with limited experience in digital image processing. This includes, for example, pre-processing, transformation and presentation of the data in a less complex structure for further data analysis. There are numerous software solutions for the analysis of foci. This review gives an overview of open source image processing software packages, including graphical user interfaces (GUIs) such as CellProfiler, Icy and ImageJ/Fiji. Software packages like CellProfiler and Icy enable to gain high-content information about DSB biomarkers. Programming languages, like Python, are discussed briefly.

A Refined Global Segmentation of X-Ray CT Images for Multi-phase Geomaterials

X-ray computed tomography images of three-phase silica sand and glass bead specimens are analyzed and used to evaluate the segmentation performances of Otsu-, and recursion-based multilevel algorithms. A global image segmentation technique that combines iterative and recursive algorithms, namely a refined statistics-based global segmentation is proposed for segmenting multi-phase granular geomaterials. The performance of the proposed algorithm is tested by segmenting partially saturated silica sand and glass bead specimens. For the tested silica sand specimen, the refined statistics method estimated void ratio and degree of saturation were 0.67 and 39.35%. The estimates for the glass bead specimen yielded 0.64 and 43.49%, respectively. The true void ratio (0.66) and degree of saturation (37.71%) were determined with a user-controlled Image processing software package—Image-Pro. It was found that the proposed method estimated the void ratio and the degree of saturation with 1.52 and 4.35 percent errors for the silica sand and with 15.63 and 0.34 percent errors for the glass bead, respectively. The computational time of the proposed method was found to be shorter than other methods considered. Overall, it is concluded that the proposed technique performed better in segmenting three-phase granular geomaterials.

Complex spatial and temporally defined myelin and axonal degeneration in Huntington disease.

Although much prior work has focused on the basal ganglia and cortical pathology that defines Huntington's disease (HD), recent studies have also begun to characterize cerebral white matter damage (Rosas et al., 2006; Dumas et al., 2012; Poudel et al., 2014). In this study, we investigated differences in the large fascicular bundles of the cerebral white matter of gene-positive HD carriers, including pre-manifest individuals and early symptomatic patients, using recently developed diffusion tractography procedures. We examined eighteen major fiber bundles in 37 patients with early HD (average age 55.2 ± 11.5, 14 male, 23 female), 31 gene-positive, motor negative pre-symptomatic HD (PHD) (average age 48.1 ± 11.5, 13 male, 18 female), and 38 healthy age-matched controls (average age 55.7 ± 8.6, 14 male, 24 female), using the TRActs Constrained by UnderLying Anatomy (TRACULA) procedure available as part of the FreeSurfer image processing software package. We calculated the mean fractional anisotropy (FA) and the mean radial (RD) and axial diffusivities (AD) for each fiber bundle. We also evaluated the relationships between diffusion measures, cognition and regional cortical thinning. We found that early changes in RD of select tracts in PHD subjects were associated with impaired performance on neuropsychological tests, suggesting that early changes in myelin might underlie early cognitive dysfunction. Finally, we found that increases in AD of select tracts were associated with regionally select cortical thinning of areas known to atrophy in HD, including the sensorimotor, supramarginal and fusiform gyrus, suggesting that AD may be reflecting pyramidal cell degeneration in HD. Together, these results suggest that white matter microstructural changes in HD reflect a complex, clinically relevant and dynamic process.

Detección de árboles dañados por plaga en bosques de Abies religiosa en la Reserva de la Biosfera Mariposa Monarca, mediante fotografías aéreas infrarroja

Forest pests are pathogens that cause mechanical or physiological damage to trees, such as deformations, disrupted growth, weakening, or even death, leading to important ecological, economic and social impacts. This study focused on the development of a technique for the detection of forest pests using infrared aerial photography. The general reflectance characteristics of healthy and damaged leaves are currently well known; Reid (1987) already described these features, with a shift toward blue and a reduced infrared reflectance as the dominant effects. As the plant disease progresses, the above effects become more apparent. The use of infrared digital aerial photographs allowed to obtain VIR (visible + infrared) images with four bands and a resolution of approximately one meter per pixel. Trees with some degree of deterioration and even dead individuals were identified and located through visual interpretation.Color and infrared digital aerial photographs captured in March 2009 were used; two cameras were used: a Nikon D2X camera for the acquisition of images in the visible range (EV), and a Canon EOS Digital Rebel camera for infrared (IR) images. Once individual photographs were processed and organized, V and IR images were superimposed using the Photoshop editing program (Adobe™) Once composite V+IR (VIR) images were obtained, those covering the sampling area were selected and georeferenced. Rectified images were required to elaborate a mosaic encompassing the sampling area. The rectified images and the final mosaic had a spatial resolution of 90 centimeters per pixel.The detection technique was designed using three methodological approaches: automatic, semi-automatic and manual processes. The semi-automatic and automatic modalities correspond to an assisted and unassisted spectral classification, respectively, while the manual method consisted in the direct observation of the photographs processed. The technique developed used as basis the photographic mosaic of the sampling area.The unassisted and assisted spectral classification technique was carried out in the ERDAS Imagine image-processing software package. For the unassisted classification, tests were carried out considering various numbers of categories: 5, 10 and 15; the assisted classification included the spectral properties of each category used for the partition to group images into five categories: healthy forest, diseased forest, Juniperus scrubland, bare soil and shaded areas.The accuracy of the technique for the detection of damaged trees was verified through field work, visiting different checkpoints where the health status of the tree was corroborated by direct observation and infrared photography at ground level.A representative sampling area of the A. religiosa forest was established in the Monarch Butterfly Biosphere Reserve (RBMM), sufficient to encompass the largest number of damaged trees, but not so large as to excessively prolong the information-processing phases and make field sampling unattainable.The analysis comprised an area of 1907 ha in Sierra Chincua, where the greatest affectation was observed in a core zone including 97 points (62%) with more than twice the density of individuals (11 trees/km2), relative to the buffer zone (4 trees/km2). This greater damage is the result of forest management policies, which have set no management (including sanitation) in the core zone.At the end of this research work, we concluded that digital aerial photographs proved useful for the detection of damaged trees in Abies religiosa forests of RBMM. It is possible to obtain multispectral images using a low-cost photographic technology that is relatively simple and widely available. Our study showed that the best method to detect damage in A. religiosa forests in RBMM is the visual interpretation of aerial photographs, yielding a detection efficiency of over 98%. The method used has a greater cost- effectiveness compared to helicopter overflight and field work. Likewise, the method developed in this research work is a contribution to the detection of forest pests.