Bilateral prediction and intersection calculation autofocus method for automated microscopy

In this paper, a bilateral prediction and intersection calculation autofocus method for automated microscopy, which obtains the in‐focus position by calculating the intersection of the predicted left and right focus measure curves located respectively in the left and right sides of the peak position of the focus measure curve, is proposed and performed. According to the autofocus method, the area including the peak position of the focus measure curve and its left and right neighbourhoods should be determined firstly, and the left and right neighbourhoods are considered as the left and right sampling areas. The left and right focus measure curves are predicted by appropriate predicting models according to the two sample sequences, which comprise the focus values by evaluating the sampled images in the left sampling area and right sampling area, respectively and their corresponding sampling positions. The intersection of the predicted left and right focus measure curves is calculated and can be considered as the in‐focus position. The autofocus can be realized by moving the focus plane of the microscope to the intersection of the predicted left and right focus measure curves. The proposed bilateral prediction and intersection calculation autofocus method is experimentally verified in an automated light microscopy for implementing microassembly and micromanipulation. The theoretical analyses have shown that the proposed bilateral prediction and intersection calculation autofocus method can not only effectively avoid the principle error caused by assuming the symmetrical focus measure curve in the autofocus methods based on curve fitting, but also eliminate the possible waver search near the peak position in the modified fast climbing servo method. The experimental results have shown that the proposed bilateral prediction and intersection calculation autofocus method possesses the merits as follows: (1) the focusing accuracy is high and slightly affected by the sampling step size and (2) the focusing speed is higher than those of the 7‐point hill‐climbing search method and the quadratic curve fitting method with a determinate focusing accuracy.     

Analysis‐preserving video microscopy compression via correlation and mathematical morphology

The large amount video data produced by multi‐channel, high‐resolution microscopy system drives the need for a new high‐performance domain‐specific video compression technique. We describe a novel compression method for video microscopy data. The method is based on Pearson's correlation and mathematical morphology. The method makes use of the point‐spread function (PSF) in the microscopy video acquisition phase. We compare our method to other lossless compression methods and to lossy JPEG, JPEG2000, and H.264 compression for various kinds of video microscopy data including fluorescence video and brightfield video. We find that for certain data sets, the new method compresses much better than lossless compression with no impact on analysis results. It achieved a best compressed size of 0.77% of the original size, 25× smaller than the best lossless technique (which yields 20% for the same video). The compressed size scales with the video's scientific data content. Further testing showed that existing lossy algorithms greatly impacted data analysis at similar compression sizes. Microsc. Res. Tech. 78:1055–1061, 2015. © 2015 Wiley Periodicals, Inc.     

MRT letter: A unified accelerated maximum likelihood technique for widefield,confocal, and super‐resolution 4Pi microscopy

We propose an algorithmic technique for accelerating maximum likelihood (ML) algorithm for image reconstruction in fluorescence microscopy. This is made possible by integrating Biggs–Andrews (BA) method with ML approach. The results on widefield, confocal, and super‐resolution 4Pi microscopy reveal substantial improvement in the speed of 3D image reconstruction (the number of iterations has reduced by approximately one‐half). Moreover, the quality of reconstruction obtained using accelerated ML closely resembles with nonaccelerated ML method. The proposed technique is a step closer to realize real‐time reconstruction in 3D fluorescence microscopy. Microsc. Res. Tech. 78:331–335, 2015. © 2015 Wiley Periodicals, Inc.     

A novel autofocusing method using the angle of hilbert space for microscopy

Autofocusing technology is indispensable for routine use of microscopes on a large scale in biological field. The autofocusing method using the angle of Hilbert space is brought forward to measure whether the image is focused or not. The angle of Hillbert space can be used to evaluate accurately the similarity degree of two images. The experiment results show that the autofocusing method can decrease the computational cost and get accuracy for real‐time biological and biomedical images with noise robustness. The focus curves are smooth and possess the unimodality, the monotonicity and the symmetry. Compared with other classic and optimum focus method, the Hilbert method demonstrates its robustness to noise and can improve the focus speed. The experiments showed that the proposed method can increase the overall performance of an autofocus system and has strong applicability in various autofocusing algorithms. Microsc. Res. Tech. 77:289–295, 2014. © 2014 Wiley Periodicals, Inc.     

A computational approach to detect and segment cytoplasm in muscle fiber images

We developed a computational approach to detect and segment cytoplasm in microscopic images of skeletal muscle fibers. The computational approach provides computer‐aided analysis of cytoplasm objects in muscle fiber images to facilitate biomedical research. Cytoplasm in muscle fibers plays an important role in maintaining the functioning and health of muscular tissues. Therefore, cytoplasm is often used as a marker in broad applications of musculoskeletal research, including our search on treatment of muscular disorders such as Duchenne muscular dystrophy, a disease that has no available treatment. However, it is often challenging to analyze cytoplasm and quantify it given the large number of images typically generated in experiments and the large number of muscle fibers contained in each image. Manual analysis is not only time consuming but also prone to human errors. In this work we developed a computational approach to detect and segment the longitudinal sections of cytoplasm based on a modified graph cuts technique and iterative splitting method to extract cytoplasm objects from the background. First, cytoplasm objects are extracted from the background using the modified graph cuts technique which is designed to optimize an energy function. Second, an iterative splitting method is designed to separate the touching or adjacent cytoplasm objects from the results of graph cuts. We tested the computational approach on real data from in vitro experiments and found that it can achieve satisfactory performance in terms of precision and recall rates. Microsc. Res. Tech. 78:508–518, 2015. © 2015 Wiley Periodicals, Inc.     

A facile method to compare EFTEM maps obtained from materials changing composition over time

Energy Filtered Transmission Electron Microscopy (EFTEM) is an analytical tool that has been successfully and widely employed in the last two decades for obtaining fast elemental maps in TEM mode. Several studies and efforts have been addressed to investigate limitations and advantages of such technique, as well as to improve the spatial resolution of compositional maps. Usually, EFTEM maps undergo post‐acquisition treatments by changing brightness and contrast levels, either via dedicated software or via human elaboration, in order to maximize their signal‐to‐noise ratio and render them as visible as possible. However, elemental maps forming a single set of EFTEM images are usually subjected to independent map‐by‐map image treatment. This post‐acquisition step becomes crucial when analyzing materials that change composition over time as a consequence of an external stimulus, because the map‐by‐map approach doesn't take into account how the chemical features of the imaged materials actually progress, in particular when the investigated elements exhibit very low signals. In this article, we present a facile procedure applicable to whole sets of EFTEM maps acquired on a sample that is evolving over time. The main aim is to find a common method to treat the images features, in order to make them as comparable as possible without affecting the information there contained. Microsc. Res. Tech. 78:1090–1097, 2015. © 2015 Wiley Periodicals, Inc.     

Automatic setae segmentation from Chaetoceros microscopic images

A novel image processing model Grayscale Surface Direction Angle Model (GSDAM) is presented and the algorithm based on GSDAM is developed to segment setae from Chaetoceros microscopic images. The proposed model combines the setae characteristics of the microscopic images with the spatial analysis of image grayscale surface to detect and segment the direction thin and long setae from the low contrast background as well as noise which may make the commonly used segmentation methods invalid. The experimental results show that our algorithm based on GSDAM outperforms the boundary‐based and region‐based segmentation methods Canny edge detector, iterative threshold selection, Otsu's thresholding, minimum error thresholding, K‐means clustering, and marker‐controlled watershed on the setae segmentation more accurately and completely. Microsc. Res. Tech. 77:684–690, 2014. © 2014 Wiley Periodicals, Inc.     

Fast,high-precision autofocus on a motorised microscope: Automating blood sample imaging on the OpenFlexure Microscope

The OpenFlexure Microscope is a 3D-printed, low-cost microscope capable of automated image acquisition through the use of a motorised translation stage and a Raspberry Pi imaging system. This automation has applications in research and healthcare, including in supporting the diagnosis of malaria in low-resource settings. The plasmodium parasites that cause malaria require high magnification imaging, which has a shallow depth of field, necessitating the development of an accurate and precise autofocus procedure. We present methods of identifying the focal plane of the microscope, and procedures for reliably acquiring a stack of focused images on a system affected by backlash and drift. We also present and assess a method to verify the success of autofocus during the scan. The speed, reliability and precision of each method are evaluated, and the limitations discussed in terms of the end users' requirements.     

光学显微镜自动聚焦的技术研究

在对普通光学显微镜进行一定改装的基础之上 ,设计了一套显微镜自动聚焦系统 ,并且给出了图像的灰度差分绝对值之和算子 ,解决了自动聚焦过程中是否正确聚焦的判断问题。最后还给出了一套基于启发式搜索算法的聚焦搜索策略 ,以加快焦平面的搜索。     

An effective and accurate identification system of Mycobacterium tuberculosis using convolution neural networks

Tuberculosis (TB) remains the leading cause of morbidity and mortality from infectious disease in developing countries. The sputum smear microscopy remains the primary diagnostic laboratory test. However, microscopic examination is always time‐consuming and tedious. Therefore, an effective computer‐aided image identification system is needed to provide timely assistance in diagnosis. The current identification system usually suffers from complex color variations of the images, resulting in plentiful of false object detection. To overcome the dilemma, we propose a two‐stage Mycobacterium tuberculosis identification system, consisting of candidate detection and classification using convolution neural networks (CNNs). The refined Faster region‐based CNN was used to distinguish candidates of M. tuberculosis and the actual ones were classified by utilizing CNN‐based classifier. We first compared three different CNNs, including ensemble CNN, single‐member CNN, and deep CNN. The experimental results showed that both ensemble and deep CNNs were on par with similar identification performance when analyzing more than 19,000 images. A much better recall value was achieved by using our proposed system in comparison with conventional pixel‐based support vector machine method for M. tuberculosis bacilli detection.     

Orientational analysis of planar fibre systems observed as a Poisson shot-noise process

We consider two‐dimensional fibrous materials observed as a digital greyscale image. The problem addressed is to estimate the orientation distribution of unobservable thin fibres from a greyscale image modelled by a planar Poisson shot‐noise process. The classical stereological approach is not straightforward, because the point intensities of thin fibres along sampling lines may not be observable. For such cases, Kärkkäinen et al. (2001) suggested the use of scaled variograms determined from grey values along sampling lines in several directions. Their method is based on the assumption that the proportion between the scaled variograms and point intensities in all directions of sampling lines is constant. This assumption is proved to be valid asymptotically for Boolean models and dead leaves models, under some regularity conditions. In this work, we derive the scaled variogram and its approximations for a planar Poisson shot‐noise process using the modified Bessel function. In the case of reasonable high resolution of the observed image, the scaled variogram has an approximate functional relation to the point intensity, and in the case of high resolution the relation is proportional. As the obtained relations are approximative, they are tested on simulations. The existing orientation analysis method based on the proportional relation is further experimented on images with different resolutions. The new result, the asymptotic proportionality between the scaled variograms and the point intensities for a Poisson shot‐noise process, completes the earlier results for the Boolean models and for the dead leaves models.     

Removing noises caused by motion artefacts in microcirculation maps of human skin in vivo

This paper presents a zero‐padding and cross‐correlation technique‐based correlation mapping optical coherence tomography (ZPCC‐cmOCT) to reconstruct microcirculation maps of human skin in vivo, which can remove the background decorrelation noise caused by motion artefacts. In conventional correlation mapping optical coherence tomography method, the correlation degree of static tissue may be lowered by the motion artefacts due to cardiac and respiratory motion, resulting in background decorrelation noise in microcirculation maps. In zero‐padding and cross‐correlation technique‐based correlation mapping optical coherence tomography method, structural images are first obtained by performing Fourier transform on zero‐padded interference fringes, and then cross‐correlation‐based image registration is utilized to align local areas in two adjacent structural images. Finally, correlation mapping optical coherence tomography method is performed to generate microcirculation maps. Both phantom experiments and in vivo experiments were implemented and the results demonstrate that the proposed method is capable of providing microcirculation maps with the background decorrelation noise removed.     

A fast autofocus sharpness function of microvision system based on the Robert function and Gauss fitting

For the microvision system, a new autofocus evaluation function based on the Robert function is proposed by increasing the threshold value. Compared with the traditional evaluation function, the new focus function reduces the local extreme value and increases the steepness of the focusing curve. According to the characteristics of the focusing evaluation function, the focus curve can be divided into two stages: the gentle area and the steep area. In the gentle area, there will be set a large step‐length to realize the fast search. In the steep area, the data will be fitted by Gauss method, and on the basis of the fitting results, the motor of microvision system was directly driven to achieve the focal plane and this method has been improved in real‐time and accuracy.     

A simple and stable autofocusing protocol for long multidimensional live cell microscopy

Focus maintenance is a challenging problem in multidimensional wide‐field microscopy. Most automated microscopes use software algorithms, which are applied to z‐sections of the object, to select for the plane with the best signal to noise ratio. When applied automatically in multidimensional imaging applications, autofocus routines significantly increase light exposure and can become cytotoxic if applied too frequently. In addition, automated focusing procedures can readily focus on unwanted high contrast objects. By labelling a defined position with a fluorescent marker, we were able to separate the focusing procedure from the actual image acquisition positions and therefore overcome some of the major drawbacks of routine autofocus procedures. To implement this method in a multidimensional acquisition experiment, we created a visual basic‐based program, which is run prior to each image acquisition. This technique allows tight control of focus whilst keeping light toxicity in live cell imaging experiments to a minimum.     

Directional analysis of digitized three-dimensional images by configuration counts

A method for estimating the orientated rose of normal directions of a three‐dimensional (3D) set Z from a digitization of Z, i.e. a voxel image, is presented. It is based on counts of informative configurations in n×n×n voxel cubes. An algorithm for finding all informative configurations is proposed and an estimation procedure is described in detail for the case n= 2. The presented method is a 3D version of a method of estimating the orientated rose of binary planar images using n×n configurations. A new feature is the design‐based approach, being more appropriate for biomedical image analysis than the formerly applied model‐based approach.     

基于图像清晰度评价的跟踪望远镜自动调焦算法研究

为了减小跟踪望远镜调焦时间,分析了自动调焦的光学原理及数字图像处理相关技术,提出一种适合跟踪望远镜的实时自动调焦算法。该算法基于对图像清晰度的评价,通过步进电机驱动次镜移动来搜索最佳成像位置,并且综合了全局搜索法与传统爬山法的优点。在实验中,完成了对远处静态目标自动对焦,有效地避免了局部峰值导致的对焦失败,在保证系统调焦精度的前提下使对焦速度小于3s。     

MRT letter: Visual attention driven framework for hysteroscopy video abstraction

Diagnostic hysteroscopy is a popular method for investigating the regions in the female reproductive system. The videos generated by hysteroscopy sessions of patients are recurrently archived in medical libraries. Gynecologists often need to browse these libraries in search of similar cases or for reviewing old videos of a patient. Diagnostic hysteroscopy videos contain a lot of information with abundant redundancy. Key frame extraction‐based video summarization can be used to reduce this huge amount of data. Moreover, key frames can be used for browsing and indexing of hysteroscopy videos. In this article, a domain specific visual attention driven framework for summarization of hysteroscopy videos is proposed. The visual attention model is materialized by computing saliency based on color, texture, and motion. The experimental results, in comparison with other techniques, demonstrate the efficacy of the proposed framework. Microsc. Res. Tech. 76:559–563, 2013. © 2013 Wiley Periodicals, Inc.     

Biochemical and morphological alterations of the extracellular matrix of chicken calcaneal tendon during maturation

The region in tendons that surrounds bone extremities adapts to compression forces, developing a fibrocartilaginous structure. During maturation, changes occur in the amount and organization of macromolecules of the extracellular matrix of tendons, changing the tissue morphology. To study the effect of maturation on tendons, Pedrês chickens were sacrificed at 1, 5, and 8 months old and had the calcaneal tendon (CT) divided into proximal region, submitted to tension/compression forces ( p ), and distal region submitted to tension force ( d ). Morphological analysis of the p region showed the presence of fibrocartilage in all ages. In the central part of the fibrocartilage, near a diminishment of the metachromasy, there was also a development of a probable fat pad that increased with the maturation. The activity of MMP‐2 and MMP‐9 was higher at 5 and 8 months old, in both regions, compared with 1‐month‐old animals. In SDS‐PAGE analysis, components with electrophoretic migration similar to decorin and fibromodulin increased with maturation, particularly in the d region. The Western blotting confirmed the increased amount of fibromodulin with maturation. In conclusion, our results show that process of maturation leads to the appearance of a probable fat pad in the center of the fibrocartilage of CT, with a reduced amount of glycosaminoglycans and an increased activity of MMPs. Microsc. Res. Tech. 78:949–957, 2015. © 2015 Wiley Periodicals, Inc.     

Determination of a homogeneity factor for composite materials by a microstructural image analysis method

The physical properties of particle‐reinforced composite materials are highly affected by the distribution of particles within a matrix material. In this study, a microstructural image analysis method with a new distribution index for quantifying the degree of distribution in composite materials was developed. The free‐path spacing between particles was measured to calculate the distribution (D) index based on the coefficient of variation. The proposed method was applied to six digitally created reference patterns as representative binary composite microstructures and three actual ceramic‐matrix composites, respectively. It is found that the D index increased from 0.00 to 0.67 depending on the degree of distribution or homogeneity level based on the reference patterns. The homogeneity levels for the binary composites are then classified from a perfect (maximum) to very low level (minimum) based on increasing D index values, where a high D index presents a poorer distribution. The results obtained for reference patterns and metal silicide‐refractory oxide composite microstructures indicate that the proposed method is a useful tool to quantify the degree of distribution with high accuracy, and can be efficiently used for different types of composite microstructures.     

MRT Letter: 3D culture of isolated cells: A fast and efficient method for optimizing their histochemical and immunocytochemical analyses

The rapid development of three‐dimensional (3D) culture systems and engineered cell‐based tissue models gave rise to an increasing need of new techniques, allowing the microscopic observation of cell behavior/morphology in tissue‐like structures, as clearly signalled by several authors during the last decennium. With samples consisting of small aggregates of isolated cells grown in suspension, it is often difficult to produce an optimal embedded preparation that can be further successfully processed for classical histochemical investigations. In this work, we describe a new, easy to use, efficient method that enables to embed an enriched “preparation” of isolated cells/small 3D cell aggregates, without any cell stress or damage. As for after tissue‐embedding procedures, the cellular blocks can be further suitably processed for efficient histochemical as well as immunohistochemical analyses, rendering more informative‐and attractive‐studies onto 3D cell‐based culture of neo‐tissues. Microsc. Res. Tech. 78:249–254, 2015. © 2015 Wiley Periodicals, Inc.