Optical Image Analysis System Research Articles

Semi-automated procedure of digitalization and study of rock thin section porosity applying optical image analysis tools

A detailed description of a semi-automated process of digitalization, visualization and quantification of rock thin sections by applying Optical Image Analysis (OIA) is presented. The main goal of this process is to guarantee the reproducibility of the OIA method on images acquired by a high-resolution scanner (HRS, Cannon V850 Pro) from thin sections, emulating an optical microscope. The method consists of the following sequence of operations and functions: i) image acquisition under polarized conditions by image analysis programs (SilverFast SE Plus 8I), ii) spatial correction of images to ensure correct spatial correlation and registration by using a Geographic Information System software (QGIS 2.14.0-Essen), iii) pore identification and pore size and shape parameter quantification (ImageJ 1.50i), iv) storage of the high resolution polarized images. This semi-automated process grants effective pore segmentation based on images of different cross-polarized light conditions (90°/0°; 135°/45°) and plane-polarized light conditions (90°/-; 0°/-) of the same petrographic scene. The optical resolution of the used images (6400 dots per inch) enables the visualization of pores with diameters ranging from 3.97 μm to 2000 μm. The proposed method was applied to and tested by the quantification of optical pores of two sedimentary rocks before and after their exposure to supercritical CO2 (t: 970 h). Through this process, rock pore evolution after interaction with supercritical CO2 can be correctly assessed. The applied OIA system and, in particular, the sets of obtained high resolution polarized digital images provided a basis for the development of a remote visualization system. This system makes it possible to virtually represent thin sections similarly to a simple virtual microscope. The described workflow offers a fast, effective and reproducible methodology that could complement petrographic studies.

Novel developments in optical image analysis for iron ore, sinter and coke characterisation

A textural approach to the geometallurgical characterisation of iron ores helps better predict ore behaviour during downstream processing. Therefore, a robust, automated, objective method for the textural characterisation of iron ores is relevant to both research and industry needs. Utilisation of an optical image analysis (OIA) technique allows reliable and consistent identification of different iron oxide and oxy-hydroxide minerals, e.g. haematite, kenomagnetite, hydrohematite, both vitreous and ochreous goethite. CSIRO Mineral4/Recognition4 OIA system automatically identifies particle sections with different textures and assigns these sections to defined textural groups. Furthermore, novel developments in the system have enabled the automatic identification of different textural forms and morphologies of the same mineral, e.g. martite and microplaty haematite in iron ore; primary and secondary haematite or different types of Silico-Ferrite of Calcium and Aluminium (SFCA) in sinter as well as segmentation of different phases with the same reflectivity like Inert Maceral Derived Components (IMDC) from Reactive Maceral Derived Components (RMDC) in coke.The high resolution and imaging speed of the OIA system makes it possible for users to significantly reduce the cost and subjectivity of iron ore characterisation with a simultaneous increase in the accuracy of mineral identification. Extra software modules have been developed to meet research and industry demands for enhanced productivity. The addition of a ‘Multiple Block Imaging’ module enables image acquisition for sets of polished blocks at a time, rather than separate imaging of individual blocks. The ‘Multiple Set Processing’ module allows the processing up to 20 groups of sets simultaneously, where every group can contain up to 20 different sets of images that share the same analysis profile. The added modules enable analyses to be performed over many hours without the need for operator intervention, thus increasing equipment utilisation and reducing operator time.These new developments, together with the improvement of previously available features, e.g. identification of non-opaque minerals, automated textural classification, automated particle separation, automated correction of mineral maps and on-line measurement, means that OIA can provide a unique, reliable, industry and research focused tool for iron ore, sinter and coke characterisation.

Comparative study of iron ore characterisation using a scanning electron microscope and optical image analysis

In order to develop downstream processing routines for iron ore and to understand the behaviour of the ore during processing, extensive mineralogical characterisation is required. Microscopic analysis of polished sections is effective to determine mineral associations, mineral liberation and grain size distribution. There are two main imaging techniques used for the characterisation of iron ore, i.e. optical image analysis (OIA) and scanning electron microscopy (SEM). In this article, a QEMSCAN system is used as an example of SEM methodology and results obtained from it are compared against results obtained by the CSIRO Recognition3/Mineral3 OIA system. Both OIA and SEM systems have advantages and drawbacks. Even though the latest SEM systems can distinguish between major iron oxides and oxyhydroxides, it is still problematic for SEM systems to distinguish between iron ore minerals very close in oxygen content, e.g. hematite and hydrohematite, or between different types of goethite. Scanning electron microscopy systems also can misidentify minerals with close chemical composition, i.e. hematite as magnetite and vitreous goethite as hematite. In OIA, iron minerals with slight differences in their oxidation or hydration state are more easily and directly recognisable by correlation with their reflectivity. In both methods, the presence of microporosity can result in some misidentification, but in SEM methods misidentifications due to microporosity can be critical. Low resolution during QEMSCAN analysis can significantly affect the textural classification of particle sections. The main conclusion of this study is that, for low iron content ores or tailings, SEM systems can provide much more detailed information on the gangue minerals than OIA. However, for routine characterisation of iron ores with high iron content and containing a variety of iron oxides and oxyhydroxides, OIA is a faster, more cost effective and more reliable method of iron ore characterisation. A combined approach using both techniques will provide the most detailed understanding of iron ore samples being characterised.

On-Chip Single-Cell-Shape Control Technology for Understanding Contractile Motion of Cardiomyocytes Measured Using Optical Image Analysis System

Quantitative evaluation of mechanophysiological responses of cardiomyocytes has become more important for more precise prediction of cardiotoxicity. For the accurate detection of cardiomyocyte contraction, we have developed an on-chip single-cell-shape control technology on the basis of an agarose microchamber system and an on-chip optical image analysis system that records the contractile motions of cardiomyocytes with noninvasive/nondestructive measurement for long-term experiments. Using this on-chip single-cell-shape control technology, the shape of single cardiomyocytes was controlled by seeding the cells in 21-µm-radius (circular) or 20×70 µm2 (rectangular) agarose microchambers. To detect the contractility of cardiomyocytes, the cells were labeled with microbeads attached onto the surface of target cells and the motion of beads was acquired and analyzed using a newly developed wider-depth-of-field optics equipped with a 1/100 s high-speed digital camera. Mechanophysiological properties such as displacement and direction of movement were obtained using a real-time processing system module at spatial and temporal resolutions of 0.15 µm and 10 ms, respectively. Comparisons of displacement and direction of contraction between circular and rectangular cardiomyocytes indicated that the rectangular cardiomyocytes tended to contract along the longitudinal direction as in a real heart. This result suggests that the shape of cells affected the function of cells. The on-chip single-cell-shape control technology and optical image analysis system enable the detection of the motion of contraction of single-shape-controlled cardiomyocytes, and are expected to be applicable to the more precise prediction of cardiotoxicity.

2P287 オンチップ画像解析システムによる形状を制御した単一心筋細胞の収縮方向の計測(26.計測,ポスター,日本生物物理学会年会第51回(2013年度))

2P287 オンチップ画像解析システムによる形状を制御した単一心筋細胞の収縮方向の計測(26.計測,ポスター,日本生物物理学会年会第51回(2013年度))

Plant Tissue Degradation Measurement Using Image Analysis

AbstractSeveral microscopic techniques have been used to measure plant tissue degradation by rumen microorganisms. Our objective was to develop a less subjective method for measuring plant tissue degradation using computer‐based image analysis rather than visual appraisal. Three millimeter segments of leaf blades from ‘Cave‐In‐Rock’ switchgrass (Panicum virgatum L.) were placed either directly into a fixative or into buffered rumen fluid for 48 h. Segments were retrieved and prepared for light microscopy by fixation, dehydration, embedding, trimming, and sectioning at a thickness of 2 μ. Tissues in cross section were measured with an optical image analysis system and each tissue type was classified as undigested, partially digested, or completely digested. The relative proportion of tissue types in undigested samples ranged from 1.9 ± 0.20% for phloem tissue to 35.9 ± 1.26% for mesophyll tissue. Standard deviations of measurements from digested samples ranged from 1.1 to 12.2%. Degradation of xylem and phloem was difficult to measure and had the highest standard deviations of 9.8 and 12.2%, respectively. This method requires approximately 15 min per sample, and although it is more time consuming than visual estimation methods, it has the advantage of measuring extent of digestion on an area basis more objectively than other methods currently used.

Optical image analysis of fine coal particles as an aid in optimizing combustion in a fluidized bed

The performance of a fluidized bed combustor is adversely affected by the entrainment of fine coal and char particles. The size distribution of the entrained particles is an indicator of the combustor's performance. Size analysis data may be helpful for optimizing the operating conditions. An optical image analysis system (TAS, Leitz) was used to analyze the size distribution of char particles elutriated from a small fluidized bed after one single pass. The TAS system discriminates between highly reflecting char particles and low-reflectance ash. The maximum size of the chars produced in these experiments was about 50 μm, almost independent of the type of coal.