Cellular logic implementation on a generalized image processor applied to biomedical image processing

The implementation on a generalized image processor of a cellular logic package that performs non-recursive cellular-logic operations (CLOs) in real time is described. This system takes advantage of up to 20 512 X 512 X 8-bit memory planes within the image processor and can manipulate cells with up to 256 symbolic states. The flexibility of the image processor allows the use of an expanded cellular transition set, beyond bit-on or bit-off, as well as application-specific neighborhood configurations. The use of concurrent data-dependent global calculations, including CLO iteration termination control, is described. The array processor implementation specifics are discussed. This general cellular logic package is applied to biomedical images in the Image Processing Laboratory, Department of Radiological Sciences, University of California at Los Angeles. Geometric information is acquired from the images using real-time operators on the image array processor. This information includes image segmentation, area calculation, object counting, centroid determination and shape analysis. Initial clinical results are presented, and possible future medical applications are discussed.     

RosettaScripts: a scripting language interface to the Rosetta macromolecular modeling suite

Macromolecular modeling and design are increasingly useful in basic research, biotechnology, and teaching. However, the absence of a user-friendly modeling framework that provides access to a wide range of modeling capabilities is hampering the wider adoption of computational methods by non-experts. RosettaScripts is an XML-like language for specifying modeling tasks in the Rosetta framework. RosettaScripts provides access to protocol-level functionalities, such as rigid-body docking and sequence redesign, and allows fast testing and deployment of complex protocols without need for modifying or recompiling the underlying C++ code. We illustrate these capabilities with RosettaScripts protocols for the stabilization of proteins, the generation of computationally constrained libraries for experimental selection of higher-affinity binding proteins, loop remodeling, small-molecule ligand docking, design of ligand-binding proteins, and specificity redesign in DNA-binding proteins.     

Teaching computer interfacing with virtual instruments in an object-oriented language.

LabVIEW is a graphic object-oriented computer language developed to facilitate hardware/software communication. LabVIEW is a complete computer language that can be used like Basic, FORTRAN, or C. In LabVIEW one creates virtual instruments that aesthetically look like real instruments but are controlled by sophisticated computer programs. There are several levels of data acquisition VIs that make it easy to control data flow, and many signal processing and analysis algorithms come with the software as premade VIs. In the classroom, the similarity between virtual and real instruments helps students understand how information is passed between the computer and attached instruments. The software may be used in the absence of hardware so that students can work at home as well as in the classroom. This article demonstrates how LabVIEW can be used to control data flow between computers and instruments, points out important features for signal processing and analysis, and shows how virtual instruments may be used in place of physical instrumentation. Applications of LabVIEW to the teaching laboratory are also discussed, and a plausible course outline is given.     

基于图像处理的血液细胞特征提取

利用数学形态学知识和图像处理方法,对缺铁性贫血的血液显微图像进行了分析,编制了相应的计算程序,对选取的区域内细胞的个数、半径和面积等重要参数进行了统计和处理,这对进一步研究细胞及其组织变化、医学临床诊断等问题,具有一定的指导意义。     

GUI programs for processing individual images in early stages of helical image reconstruction--for high-resolution structure analysis

A set of programs equipped with graphical user interface has been developed for processing individual images in early stages of the three-dimensional helical image reconstruction procedure. These programs can be used for initial screening of suitable image area, straightening the object image, determination of box parameters including the repeat distance, determination of the out-of-plane tilt and initial editing of the layer-line data. These tasks are difficult to automate and therefore very time-consuming. The programs, developed by adopting the concept of the layer-line indexing [Ultramicroscopy 84 (2000) 1-14], are effective for processing many images of filamentous molecular assemblies and especially tubular crystals having various helical classes. Using these programs, higher-resolution signals can be extracted more reliably and quickly, and the time required for processing each image can be reduced to 1/2-1/10. Here also presented is an overview on helical image reconstruction for high-resolution structure analysis.     

Syntactic processing depends on dorsal language tracts

Frontal and temporal language areas involved in syntactic processing are connected by several dorsal and ventral tracts, but the functional roles of the different tracts are not well understood. To identify which white matter tract(s) are important for syntactic processing, we examined the relationship between white matter damage and syntactic deficits in patients with primary progressive aphasia, using multimodal neuroimaging and neurolinguistic assessment. Diffusion tensor imaging showed that microstructural damage to left hemisphere dorsal tracts--the superior longitudinal fasciculus including its arcuate component--was strongly associated with deficits in comprehension and production of syntax. Damage to these dorsal tracts predicted syntactic deficits after gray matter atrophy was taken into account, and fMRI confirmed that these tracts connect regions modulated by syntactic processing. In contrast, damage to ventral tracts--the extreme capsule fiber system or the uncinate fasciculus--was not associated with syntactic deficits. Our findings show that syntactic processing depends primarily on dorsal language tracts.     

Real-space processing of helical filaments in SPARX

We present a major revision of the iterative helical real-space refinement (IHRSR) procedure and its implementation in the SPARX single particle image processing environment. We built on over a decade of experience with IHRSR helical structure determination and we took advantage of the flexible SPARX infrastructure to arrive at an implementation that offers ease of use, flexibility in designing helical structure determination strategy, and high computational efficiency. We introduced the 3D projection matching code which now is able to work with non-cubic volumes, the geometry better suited for long helical filaments, we enhanced procedures for establishing helical symmetry parameters, and we parallelized the code using distributed memory paradigm. Additional features include a graphical user interface that facilitates entering and editing of parameters controlling the structure determination strategy of the program. In addition, we present a novel approach to detect and evaluate structural heterogeneity due to conformer mixtures that takes advantage of helical structure redundancy.     

XMIPP: a new generation of an open-source image processing package for electron microscopy

X-windows based microscopy image processing package (Xmipp) is a specialized suit of image processing programs, primarily aimed at obtaining the 3D reconstruction of biological specimens from large sets of projection images acquired by transmission electron microscopy. This public-domain software package was introduced to the electron microscopy field eight years ago, and since then it has changed drastically. New methodologies for the analysis of single-particle projection images have been added to classification, contrast transfer function correction, angular assignment, 3D reconstruction, reconstruction of crystals, etc. In addition, the package has been extended with functionalities for 2D crystal and electron tomography data. Furthermore, its current implementation in C++, with a highly modular design of well-documented data structures and functions, offers a convenient environment for the development of novel algorithms. In this paper, we present a general overview of a new generation of Xmipp that has been re-engineered to maximize flexibility and modularity, potentially facilitating its integration in future standardization efforts in the field. Moreover, by focusing on those developments that distinguish Xmipp from other packages available, we illustrate its added value to the electron microscopy community.     

Real time image processing with an analog vision chip system

A linear analog network model is proposed to characterize the function of the outer retinal circuit in terms of the standard regularization theory. Inspired by the function and the architecture of the model, a vision chip has been designed using analog CMOS Very Large Scale Integrated circuit technology. In the chip, sample/hold amplifier circuits are incorporated to compensate for statistic transistor mismatches. Accordingly, extremely low noise outputs were obtained from the chip. Using the chip and a zero-crossing detector, edges of given images were effectively extracted in indoor illumination.     

Membrane trafficking in guard cells during stomatal movement: Application of an image processing technique

Pairs of guard cells form small pores called stoma in the epidermis, and the reversible swelling and shrinking of these guard cells regulate the stomatal apertures. The well-documented changes in guard cell volume have been associated with their vacuolar structures. To investigate the contribution of the guard cell vacuoles to stomatal movement, the dynamics of these vacuolar structures were recently monitored during stomatal movement in vacuolar-membrane visualized Arabidopsis plants. Calculation of the vacuolar volume and surface area after reconstruction of three-dimensional images revealed a decrease in the vacuolar volume but an increase in the vacuolar surface area upon stomatal closure. These results implied the possible acceleration of membrane trafficking to the vacuole upon stomatal closure and membrane recycling from the vacuole to the plasma membrane upon stomatal opening. To clarify and quantify membrane trafficking during stomatal movement, we describe in this addendum our development of an improved image processing system.Key words: stomata, guard cells, vacuole, membrane traffic, image processing     

Theme B: Biomedical signal and image processing

This paper presents an overview of the main actions and projects of the theme B ‘Biomedical Signal and Image Processing’ of the GdR Stic-Santé. Several scientific meetings have been organized during the 2011–2012 period. They are always devoted to advanced signal and image processing that could bring innovative solutions to relevant medical applications. The theme has strong relationships with other GdRs and also organizes meetings in close coordination with these GdRs. It also supports two working groups with well-identified research projects. Prospects includes reinforcing communication and cooperation with the other GdRs, involving labs from other countries, and attracting private companies that could also share their needs in terms of developments for which the theme participants could offer solutions. The whole motivation is to enhance the fit between academic research, needs from the medical community and impact for medical research and applications.     

A hybrid image processing system for X-ray images of an external fixator

In the field of orthopaedics, treatment of extremity deformities can be realised by means of external fixators. However, control of such biomedical system is very difficult. Some different mathematical models have been developed to improve quality of this service. Most of the parameters, which are used in these models, have been obtained from two orthogonal X-ray images: one from anteroposterior, AP, direction and the other from a lateral, L, direction. The quality of the results of this model is dependent on the accuracy of the input parameters. Measuring these parameters is a time-consuming issue, and the accuracy of the results is also low. To increase the quality of the measurement, the reference points should be chosen from the edges of the biomedical system, and it is important to find the edges without noise. To achieve this purpose, Sobel edge detector, binary large object analysis, thresholding and inverting are applied as image processing steps. The results are compared with manual measurement values which have been obtained earlier. The results show that semi-automatic measurement of the parameters is more accurate and faster than manual measurement. It shows that the efficiency of the fixator method has been improved.     

A hybrid image processing system for X-ray images of an external fixator

In the field of orthopaedics, treatment of extremity deformities can be realised by means of external fixators. However, control of such biomedical system is very difficult. Some different mathematical models have been developed to improve quality of this service. Most of the parameters, which are used in these models, have been obtained from two orthogonal X-ray images: one from anteroposterior, AP, direction and the other from a lateral, L, direction. The quality of the results of this model is dependent on the accuracy of the input parameters. Measuring these parameters is a time-consuming issue, and the accuracy of the results is also low. To increase the quality of the measurement, the reference points should be chosen from the edges of the biomedical system, and it is important to find the edges without noise. To achieve this purpose, Sobel edge detector, binary large object analysis, thresholding and inverting are applied as image processing steps. The results are compared with manual measurement values which have been obtained earlier. The results show that semi-automatic measurement of the parameters is more accurate and faster than manual measurement. It shows that the efficiency of the fixator method has been improved.     

Videokymographic image processing: Objective parameters and user-friendly interface

Videolaryngostroboscopy (VLS) is undoubtedly a first choice examination technique in the diagnosis of several laryngeal pathologies. However, in case of low intensity or strong a-periodicity of the vocal sound, the VLS mechanism becomes ineffective in describing subsequent phases of the vocal cycle. To overcome such limitations, a new technique, called videokymography (VKG), was developed. VKG delivers images and displays the vibratory pattern from a single line selected from the whole VLS image, at the speed of approximately 8000 line-images/s. Despite its usefulness, parameter evaluation has been mostly based on visual inspection and no quantitative analysis of videokymographic images is commercially available at this time.This article presents the VKG-Analyser, a new tool for measuring and tracking quantitative parameters from VKG images. Specifically, the left-to-right period, amplitude and phase ratios and phase symmetry index were evaluated. The case of incomplete glottis closure, the minimum distance between folds was implemented.A digital image processing algorithm was developed and optimised for the analysis of VKG recordings that require intensity adjustment, noise removal and robust techniques for edge detection to avoid fluctuations of the grey levels in regions far from the vocal folds. The VKG-Analyser relies on a user-friendly interface that allows for the storage and retrieval of patients’ data and optimises the image analysis, according to a set of parameters that can be manually adjusted by the user.It was successfully tested on a set of synthetic images and applied to real VKG images, both in the case of complete and incomplete glottis closure.The new software tool aims to provide fast, reliable and reproducible measures. When applied to a large set of data, it can define reference values for normal and pathological cases, providing a valid support for diagnosis and evaluation of surgical effectiveness.     

Performance evaluation of image processing algorithms on the GPU

The graphics processing unit (GPU), which originally was used exclusively for visualization purposes, has evolved into an extremely powerful co-processor. In the meanwhile, through the development of elaborate interfaces, the GPU can be used to process data and deal with computationally intensive applications. The speed-up factors attained compared to the central processing unit (CPU) are dependent on the particular application, as the GPU architecture gives the best performance for algorithms that exhibit high data parallelism and high arithmetic intensity. Here, we evaluate the performance of the GPU on a number of common algorithms used for three-dimensional image processing. The algorithms were developed on a new software platform called "CUDA", which allows a direct translation from C code to the GPU. The implemented algorithms include spatial transformations, real-space and Fourier operations, as well as pattern recognition procedures, reconstruction algorithms and classification procedures. In our implementation, the direct porting of C code in the GPU achieves typical acceleration values in the order of 10-20 times compared to a state-of-the-art conventional processor, but they vary depending on the type of the algorithm. The gained speed-up comes with no additional costs, since the software runs on the GPU of the graphics card of common workstations.     

Bsoft: image and molecular processing in electron microscopy

Software for the processing of electron micrographs in structural biology suffers from incompatibility between different packages, poor definition and choice of conventions, and a lack of coherence in software development. The solution lies in adopting a common philosophy of interaction and conventions between the packages. To understand the choices required to have such common interfaces, I am developing a package called "Bsoft." Its foundations lie in the variety of different image file formats used in electron microscopy-a continually frustrating experience to the user and programmer alike. In Bsoft, this problem is greatly diminished by support for many different formats (including MRC, SPIDER, IMAGIC, SUPRIM, and PIF) and by separating algorithmic issues from image format-specific issues. In addition, I implemented a generalized functionality for reading the tag-base STAR (self-defining text archiving and retrieval) parameter file format as a mechanism to exchanging parameters between different packages. Bsoft is written in highly portable code (tested on several Unix systems and under VMS) and offers a continually growing range of image processing functionality, such as Fourier transformation, cross-correlation, and interpolation. Finally, prerequisites for software collaboration are explored, which include agreements on information exchange and conventions, and tests to evaluate compatibility between packages.     

Analysis of pigmentation in individual cultured plant cells using an image processing system

Anthocyanin accumulation in strawberry (Fragaria ananassa) cells cultured on a solid medium was monitored using an image-processing system that did not require direct sampling or destruction of the cells. Because of the intercellular heterogeneity of secondary metabolite production in plant cell cultures, the maximum metabolite concentration in individual cells is often more than 10 times higher than that of the average concentration. An image-processing based method enabled the growth and the pigmentation behavior of individual cells to be traced. Changes in the time courses of the anthocyanin content of individual cells differed from each other, although the average anthocyanin contents increased gradually with time in a batch culture. However, these various changing patterns in the anthocyanin content of each cell were independent of the cell cycle. In addition, image analysis revealed that the two cells just after cell division were almost identical to each other both in size and anthocyanin content. The proposed method which uses an image-processing system provides a useful tool for analyzing the secondary metabolism in individual cultured plant cells.     

Prediction of enhancer-promoter interactions via natural language processing

Background

Precise identification of three-dimensional genome organization, especially enhancer-promoter interactions (EPIs), is important to deciphering gene regulation, cell differentiation and disease mechanisms. Currently, it is a challenging task to distinguish true interactions from other nearby non-interacting ones since the power of traditional experimental methods is limited due to low resolution or low throughput.

Results

We propose a novel computational framework EP2vec to assay three-dimensional genomic interactions. We first extract sequence embedding features, defined as fixed-length vector representations learned from variable-length sequences using an unsupervised deep learning method in natural language processing. Then, we train a classifier to predict EPIs using the learned representations in supervised way. Experimental results demonstrate that EP2vec obtains F1 scores ranging from 0.841~?0.933 on different datasets, which outperforms existing methods. We prove the robustness of sequence embedding features by carrying out sensitivity analysis. Besides, we identify motifs that represent cell line-specific information through analysis of the learned sequence embedding features by adopting attention mechanism. Last, we show that even superior performance with F1 scores 0.889~?0.940 can be achieved by combining sequence embedding features and experimental features.

Conclusions

EP2vec sheds light on feature extraction for DNA sequences of arbitrary lengths and provides a powerful approach for EPIs identification.