From 3-D Light Microscopic Images to Quantitative Insight

1999 ◽  
Vol 5 (S2) ◽  
pp. 524-525
Author(s):  
B. Roysam ◽  
A. Can ◽  
H. Shen ◽  
K. Al-Kofahi ◽  
J.N. Turner
Keyword(s):  
Image Analysis ◽  
Three Dimensional ◽  
Image Data ◽  
Depth Of Field ◽  
Analysis Techniques ◽  
Core Set ◽  
Spatial Dimensions ◽  
Computational Resources ◽  
Image Analysis Techniques ◽  
Mouse Lymphoma

This presentation will describe a common core set of widely applicable image analysis techniques for automated quantitative analysis of volumetric microscope image data. Volumetric (as distinct from stereoscopic) three-dimensional (3-D) Microscopy is a rapidly maturing field offering the ability to image thick (compared to the depth of field) specimens using a variety of instrumentation techniques, and producing arrays of brightness values in three spatial dimensions. Also well developed are methods to correct the acquired images for a variety of physical effects including blur and attenuation.Commonly, what is of interest is the best-possible visualization of thick specimens. The next step, increasingly being considered in view of growing computational resources, and progress in image analysis techniques, seeks to quantify many of the processes and effects being studied. In some mainstream fields, such quantitation is essential. For instance, various assays for substance testing in pharmaceutical and chemical industries involve quantitative end points. As an illustration, the Draize assay for ocular irritancy testing of drugs and biochemical products for human use requires counting of live and dead cells that stain differently. Another example is the mouse lymphoma test that requires a 3-D counting of bacterial colonies. Neurobiological assays require morphometry, as well as quantification of changes in neurons as a function of time and various applied stimuli such as drugs, heat, and radiation. Angiogenesis assays require quantification of changes in vascular morphometry. Computerized image analysis is a powerful tool for extracting quantitative data from 3-D images for statistical analysis.

Using image content for retrieval and navigation

1998 ◽  
Vol 10 (1-3) ◽  
pp. 112-119
Author(s):  
Paul H. Lewis ◽  
Hugh C. Davis ◽  
Mark R. Dobie ◽  
Wendy Hall
Keyword(s):  
Image Analysis ◽  
Image Retrieval ◽  
Multimedia Information ◽  
Visual Information ◽  
World Wide ◽  
Image Data ◽  
Analysis Techniques ◽  
The World ◽  
Information Collections ◽  
Image Analysis Techniques

Multimedia information collections are becoming increasingly common in the humanities. This paper describes developments in hypermedia and image analysis techniques which are beginning to provide tools for retrieving and navigating through digitally stored visual information. The use of static links for navigating from text has become increasingly popular with the emergence of the World Wide Web, but generic links based on information content matching can provide more powerful information handling capabilities. We show how content based retrieval and generic Unk authoring and following can be applied to image data in multimedia collections. The paper highlights some of the problems with content based techniques applied to image retrieval and navigation and suggests how the introduction of a multimedia thesaurus can overcome some of these problems. The multimedia thesaurus provides a network of concepts in the domain of interest.

High-speed brightfield 3-D imaging and 3-D image analysis of thick and overlapped cell clusters in cytological preparations

1994 ◽  
Vol 52 ◽  
pp. 218-219
Author(s):  
Robert W. Mackin
Keyword(s):  
Image Analysis ◽  
High Speed ◽  
Three Dimensional ◽  
Image Data ◽  
Ccd Camera ◽  
Objective Lens ◽  
Array Processor ◽  
Vaginal Smears ◽  
Low Contrast ◽  
Computer Controlled

This paper presents two advances towards the automated three-dimensional (3-D) analysis of thick and heavily-overlapped regions in cytological preparations such as cervical/vaginal smears. First, a high speed 3-D brightfield microscope has been developed, allowing the acquisition of image data at speeds approaching 30 optical slices per second. Second, algorithms have been developed to detect and segment nuclei in spite of the extremely high image variability and low contrast typical of such regions. The analysis of such regions is inherently a 3-D problem that cannot be solved reliably with conventional 2-D imaging and image analysis methods.High-Speed 3-D imaging of the specimen is accomplished by moving the specimen axially relative to the objective lens of a standard microscope (Zeiss) at a speed of 30 steps per second, where the stepsize is adjustable from 0.2 - 5μm. The specimen is mounted on a computer-controlled, piezoelectric microstage (Burleigh PZS-100, 68/μm displacement). At each step, an optical slice is acquired using a CCD camera (SONY XC-11/71 IP, Dalsa CA-D1-0256, and CA-D2-0512 have been used) connected to a 4-node array processor system based on the Intel i860 chip.

Going Beyond 3-D Imaging: Automated 3-D Montaged image Analysis of Cytological Specimens

1996 ◽  
Vol 54 ◽  
pp. 282-283
Author(s):  
Badrinath Roysam ◽  
Hakan Ancin ◽  
Douglas E. Becker ◽  
Robert W. Mackin ◽  
Matthew M. Chestnut ◽  
...  
Keyword(s):  
Image Analysis ◽  
Structural Changes ◽  
Sampling Methods ◽  
Spatial Clustering ◽  
Three Dimensional ◽  
Field Of View ◽  
Cell Counting ◽  
Depth Of Field ◽  
Tissue Cell ◽  
Tissue Organization

This paper summarizes recent advances made by this group in the automated three-dimensional (3-D) image analysis of cytological specimens that are much thicker than the depth of field, and much wider than the field of view of the microscope. The imaging of thick samples is motivated by the need to sample large volumes of tissue rapidly, make more accurate measurements than possible with 2-D sampling, and also to perform analysis in a manner that preserves the relative locations and 3-D structures of the cells. The motivation to study specimens much wider than the field of view arises when measurements and insights at the tissue, rather than the cell level are needed.The term “analysis” indicates a activities ranging from cell counting, neuron tracing, cell morphometry, measurement of tracers, through characterization of large populations of cells with regard to higher-level tissue organization by detecting patterns such as 3-D spatial clustering, the presence of subpopulations, and their relationships to each other. Of even more interest are changes in these parameters as a function of development, and as a reaction to external stimuli. There is a widespread need to measure structural changes in tissue caused by toxins, physiologic states, biochemicals, aging, development, and electrochemical or physical stimuli. These agents could affect the number of cells per unit volume of tissue, cell volume and shape, and cause structural changes in individual cells, inter-connections, or subtle changes in higher-level tissue architecture. It is important to process large intact volumes of tissue to achieve adequate sampling and sensitivity to subtle changes. It is desirable to perform such studies rapidly, with utmost automation, and at minimal cost. Automated 3-D image analysis methods offer unique advantages and opportunities, without making simplifying assumptions of tissue uniformity, unlike random sampling methods such as stereology.12 Although stereological methods are known to be statistically unbiased, they may not be statistically efficient. Another disadvantage of sampling methods is the lack of full visual confirmation - an attractive feature of image analysis based methods.

A Review on Automatic Bill of Material Generation and Visual Inspection on PCBs

2019 ◽  
Author(s):  
Mukhil Azhagan M. S ◽  
Dhwani Mehta ◽  
Hangwei Lu ◽  
Sudarshan Agrawal ◽  
Mark Tehranipoor ◽  
...  
Keyword(s):  
Image Analysis ◽  
Visual Inspection ◽  
Automated System ◽  
Imaging Modalities ◽  
Future Research ◽  
Analysis Techniques ◽  
Bill Of Materials ◽  
Pros And Cons ◽  
Index Terms ◽  
Image Analysis Techniques

Abstract Globalization and complexity of the PCB supply chain has made hardware assurance a challenging task. An automated system to extract the Bill of Materials (BoM) can save time and resources during the authentication process, however, there are numerous imaging modalities and image analysis techniques that can be used to create such a system. In this paper we review different imaging modalities and their pros and cons for automatic PCB inspection. In addition, image analysis techniques commonly used for such images are reviewed in a systematic way to provide a direction for future research in this area. Index Terms—Component Detection, PCB, Authentication, Image Analysis, Machine Learning

scholarly journals Quality Evaluation of Potato Tubers Using Neural Image Analysis Method

Agriculture ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 112 ◽  
Author(s):  
Andrzej Przybylak ◽  
Radosław Kozłowski ◽  
Ewa Osuch ◽  
Andrzej Osuch ◽  
Piotr Rybacki ◽  
...  
Keyword(s):  
Image Analysis ◽  
Neural Model ◽  
Assessment Method ◽  
Analysis Method ◽  
Potato Tubers ◽  
Specialized Knowledge ◽  
Analysis Techniques ◽  
Quality Assessment Method ◽  
Sorting Process ◽  
Image Analysis Techniques

This paper describes the research aimed at developing an effective quality assessment method for potato tubers using neural image analysis techniques. Nowadays, the methods used to identify damage and diseases are time-consuming, require specialized knowledge, and often rely on subjective judgment. This study showed the use of the developed neural model as a tool supporting the evaluation of potato tubers during the sorting process in the storage room.

scholarly journals Using PhotoCube as an extensible demonstration platform for advanced image analysis techniques

2012 ◽  
Author(s):  
Grimur Tomasson ◽  
Gisli Kristjan Olafsson ◽  
Hlynur Sigurporsson ◽  
Bjorn Por Jonsson ◽  
Kristjan Runarsson ◽  
...  
Keyword(s):  
Image Analysis ◽  
Analysis Techniques ◽  
Image Analysis Techniques
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