Morphometric requirements for image analysis and the IBAS interactive automatic image analysis system

The morphometric demands made on an image analysis system are discussed, as is the IBAS interactive automatic system, which meets those requirements. The modular design of the IBAS image analysis system, with its tailor-made processors for image processing, system control and pattern recognition, gives speed and flexibility. The IMAGE image analysis language guarantees user friendliness, and, last but not least, the enormous amount of software offers accurate, reproducible measurements and dedicated evaluation programs.     

An automatic system for chromosomal analysis applied to prenatal diagnosis

Summary Computer-assisted metaphase analysis for prenatal diagnosis can be economically performed by a preexisting hardware-software system. The program can be run by technician-level (i.e., nonspecialist) personnel who can opt for the automatic operational mode for good quality metaphases or for the semimanual mode for problem metaphases (numerous superpositions, artifacts, etc.). The karyotype can be obtained in conversational mode. Hardcopy output is available for all modes.     

An automatic block and spot indexing with k-nearest neighbors graph for microarray image analysis

MOTIVATION: In this paper, we propose a fully automatic block and spot indexing algorithm for microarray image analysis. A microarray is a device which enables a parallel experiment of ten to hundreds of thousands of test genes in order to measure gene expression. Due to this huge size of experimental data, automated image analysis is gaining importance in microarray image processing systems. Currently, most of the automated microarray image processing systems require manual block indexing and, in some cases, spot indexing. If the microarray image is large and contains a lot of noise, it is very troublesome work. In this paper, we show it is possible to locate the addresses of blocks and spots by applying the Nearest Neighbors Graph Model. Also, we propose an analytic model for the feasibility of block addressing. Our analytic model is validated by a large body of experimental results. RESULTS: We demonstrate the features of automatic block detection, automatic spot addressing, and correction of the distortion and skewedness of each microarray image.     

Method of automatic recording and analysis of leukocyte migration based on the image analysis system

The method of automatic registration and of the analysis of neutrophils' mobility with the use of the Image Analysis System is described in this paper. The authors developed an algorithm of cells identification which makes it possible to carry out cadre-by-cadre observing the shift of each cell's centre of gravity with the time interval between cadres more than 15 seconds. This algorithm also allows to measure areas, perimeters and orientation of cells and their changes. Looking after the shifts of the cells' centres of gravity allows to describe the cells' paths in the form of the following dependences: path-by-time, shift-by-time, angle of vector of shift alteration. Observing a great number of cells at the same time allows to get true statistical picture of neutrophils' activity and distribution of cells' activity in population of neutrophils during only some minutes of registration. It is shown that each cell in the population has its own constant velocity.     

Software package for automatic microarray image analysis (MAIA)

Although various software solutions are currently available for microarray image analysis, one would still expect to develop algorithms ensuring higher level of intelligence and robustness. We present a fully functional software package for automatic processing of the two-color microarray images including spot localization, quantification and quality control. The developed algorithms aim at making ratio estimates more resistant to array contamination and offer automatic tools to evaluate spot quality. Availability: A demo version of the software can be downloaded from http://bioinfo.curie.fr/projects/maia. A full version is freely available to non-commercial users upon request from the authors.     

An HPLC system for the automatic sampling and analysis of time-series kinetic studies

Robotics were used to automate a high performance liquid chromatography (HPLC) system which was designed for the unattended sampling and analysis of time-series kinetic studies. The system allowed for the direct injection of samples containing whole cells and particulates witout plugging the analytical column. Coarse debris was removed from the injected sample by a 0.5 μm inline filter. Finer particulates were removed by a guard column that was layered with three different size packing resins. To demonstrate the system's capabilities, data are presented from an 8 day progress curve showing the anaerobic biodegradation of p-cresol by a sulfate-reducing enrichment. On fitting the data to the Michaelis-Menten equation by nonlinear regression, the apparent kinetic constants K_m and V_max were calculated to be 126 μM and 4.0 μM/h, respectively, for p-cresol metabolism by the enrichment.     

An experimental system for the automatic tracking and analysis of rotifer swimming behaviour

An automatic tracking system for rotifer swimming movements is described. The x and y coordinates of the Center of gravity of the animal are stored in the computer memory every twelfth of a second. Computer programs were developed to analyze the data and to calculate the average and the standard deviation for the following parameters per unit of time: distance traveled, turning angles toward the right and toward the left, distance from the point of departure as the crow flies. Histograms are traced by the computer showing the distribution of these values, as well as their evolution with time. This experimental system is dependable. The first values which we obtained for the swimming speed of rotifers correspond well with those which are given in the literature. The other parameters had not been measured until now.     

An automatic image registration scheme using Tsallis entropy

We have investigated the registration of mammograms based on the Tsallis entropy using mutual information measure. Tsallis entropy has one more parameter ‘q’ and the values of ‘q’ decide the quality of the registration. Existing Tsallis entropy based algorithms are not automatic as they claimed to be. In this article, an automatic affine image registration based on Tsallis entropy is proposed and its performance is analyzed for clinically acquired mammograms for globally registering them. The accuracy is compared with traditionally used mutual information and normalized mutual information based on Shannon entropy. Our algorithm shows promising results with increased accuracy with reduction in number of evaluations. Further, the need for pre-registration in mammogram is discussed in detail. Through this experiment, it is found that the proposed algorithm is effective enough to replace Shannon and existing Tsallis entropy based affine registration schemes.     

An approach to automatic blood vessel image registration of microcirculation for blood flow analysis on nude mice

Image registration is often a required and a time-consuming step in blood flow analysis of large microscopic video sequences in vivo. In order to obtain stable images for blood flow analysis, frame-to-frame image matching as a preprocessing step is a solution to the problem of movement during image acquisition. In this paper, microscopic system analysis without fluorescent labelling is performed to provide precise and continuous quantitative data of blood flow rate in individual microvessels of nude mice. The performance properties of several matching metrics are evaluated through simulated image registrations. An automatic image registration programme based on Powell's optimisation search method with low calculation redundancy was implemented. The matching method by variance of ratio is computationally efficient and improves the registration robustness and accuracy in practical application of microcirculation registration. The presented registration method shows acceptable results in close requisition to analyse red blood cell velocities, confirming the scientific potential of the system in blood flow analysis.     

An image analysis system for cervical cytology automation using nuclear DNA content.

An experimental computer/image analysis system has been used to investigate cytology automation techniques based on nuclear DNA measurement and morphological artefact rejector tests. The system automatically measures and normalizes the integrated optical density of cell nuclei in specially prepared cervical cytology specimens, and selects any objects with abnormally high values for further analysis. These are then analyzed by morphological and densitometric tests designed to eliminate false positive signals caused by non-nuclear artefacts. The coordinates of the remaining abnormal nuclei are recorded so that they can subsequently be relocated and examined by a cytotechnician. Preliminary results are given showing the measurement accuracy of the system and the performance of the artefact rejection tests.     

An expert system for the early detection of melanoma using knowledge-based image analysis

Melanoma is the most lethal skin cancer; however, nearly all patients can be saved and cured by early detection and prompt surgical treatment. It has been demonstrated that the major diagnostic and prognostic parameters of melanoma are the vertical thickness, three-dimensional (3D) size and shape, and color of the lesion. The other characteristic features of early melanoma are irregularities in the boundary of the lesion and the appearance of nonuniform pigmentation (with a variety of color). During early stages of development of the melanoma, the changes in these parameters are very difficult to assess since no good tool exists for measuring them in situ and analyzing them for malignancy. A novel optical instrument called the "Nevoscope" has been developed to obtain multiple views of the transilluminated skin lesion from several angles. These views have been used to measure the thickness and 3D size of the skin lesion without excision. A knowledge-based image analysis and interpretation system is being developed to analyze images of the skin lesion for a set of diagnostic and prognostic features: thickness, 3D size, color and margin, boundary and surface characteristics. This analysis combined with the patient's history, such as occurrence of melanoma or dysplastic nevi in the family, life style, skin type, etc., is used by the knowledge-based expert system to detect early or potentially malignant lesions. The diagnostic and prognostic knowledge bases for the early detection of melanoma are being developed with the help of expert dermatologists and published case studies.     

谷氨酸发酵过程葡萄糖自动流加系统

补料（流加葡萄糖）操作是谷氨酸发酵过程最重要的操作之一,工业上有各种各样的补料操作方法。控制葡萄糖浓度于一个较为平稳且适中的水平有利于提高谷氨酸发酵的性能指标。通过在线计量谷氨酸发酵中的氨水耗量并据此在线推定发酵液中的葡萄糖浓度,构建了一个谷氨酸发酵自动在线补料系统。使用该控制系统,谷氨酸发酵过程的葡萄糖浓度可以控制在任意水平,平稳、无波动的谷氨酸发酵可以得到实现。     

An automatic objective estimation of vascularization of normal and tumor-invaded brain tissue using image analysis

A rapid method for the estimation of vascularization of normal and tumor-invaded brain tissue is described. The method involves immunostaining of cryostat sections using antibodies directed against a vascular protein (type IV collagen) and an objective measurement of these vascular elements using an automatic image processing system. Significant differences between tissues of normal brains and two tumors were shown. The potential of this method with regard to forming an index of malignancy is discussed.     

A general robot control system for automatic chemical analysis

Advances in instrumentation have led to increasing interest in automatic chemical analyses. Unfortunately, the potential flexibility of robot systems can often not be exploited because of complex programming languages and poor user-interface. These factors generally limit the use of laboratory robots to a few repetitive tasks. This paper describes the development of a general robot control system for automatic chemical analysis. The program is written in Turbo Pascal and Visual Basic and runs in the Microsoft Windows environment. The analytical workspace is designed by selection of an object's icon followed by its desired orientation. Positioning of this object is then performed using a ‘drag and drop’ procedure. The robotic procedure is set-up by selection of items of apparatus and their associated actions. The performance of the system is demonstrated by the determination for caffeine in tablet formulations using a continuous dilution and calibration scheme.