Automated Image Processing for Cells and Tissue

Preston, Kendall; Bartels, Peter H.

doi:10.1007/978-1-4612-3866-9_1

Cited by 10 publications

(4 citation statements)

References 303 publications

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“…A detailed cancer diagnosis is not possible without histological classification and grading of the disease, information closely related t o therapy and prognosis for several malignancies. The grading of cancer and preneoplastic lesions can be per-formed with automated image analysing systems, and is more reproducible and more standardized than conventional grading by pathologists (2,7,8).…”

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confidence: 99%

Long distance image transfer: First results of its use in histopathological diagnosis

Kayser¹,

Oberholzer

WeißZe

et al. 1991

APMIS

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Institute of Toxicology, E. Merck, Darmstadt, 41nstitute of Toxicology, Boehringer, Ingelheim Kayser, K., Oberholzer, M., WeiDe, G., WeiDe, I. & v. Eberstein, H. Long distance image transfer: First results of its use in histopathological diagnosis. APMIS 99: 808-814, 1991. Histopathological images were transferred by use of normal telephone lines between three pathology institutes located in three different cities in the FRG. Images were digitized using a colour TV camera and stored in a special computerized image transmission system. The stored image was transferred and visualized on a (receiver) colour TV screen after dialing the telephone number connected to the receiver image transmission system. An additional telephone dialogue was activated by use of a normal acoustic telephone, and the diagnostic difficulties of the underlying image were discussed. Diagnostic assistance was possible in all transferred cases as well as histopathological diagnosis. Resolution of the images was set at 512x512 pixelx8 bit. Image transfer time was 3.2 min on average. The differences between the original and transferred image were measured by "retransfer" of the original image and by subtracting the two images from each other. No major transfer errors could be measured.

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confidence: 99%

Long distance image transfer: First results of its use in histopathological diagnosis

Kayser¹,

Oberholzer

WeißZe

et al. 1991

APMIS

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“…Transmission of these conceptual ideas to the computer and performance of the related instructions by the computer. 3. Evaluation of the result which may be available in the form of an image or in another representation .…”

Section: Software Demandsmentioning

confidence: 99%

<title>Image analysis software and sample preparation demands</title>

Roth

Wenzelides

Wolf

et al. 1990

Medtech '89: Medical Imaging

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Image analysis offers the opportunity to analyse many processes in medicine, biology and engeneering in a quantitative manner. Experience shows that it is only by awareness of preparation methods and attention to software design that full benefit can be reaped from a picture processing system in the fields of cytology and histology. Some examples of special stains for automated analysis are given here and the effectiveness of commercially available software packages is investigated.The application of picture processing and development of related special hardware and software has been increasing within the last years. As PC-based picture processing systems can be purchased at reasonable costs more and more users are confronted with these problems. Experience shows that the quality of commercially available software packages differ and the requirements on the sample preparation needed for successful problem solutions are often underestimated. But as always, sample preparation is still the key to success in automated image analysis for cells and tissues. Hence, a problem solution requires the permanent interaction between sample preparation methods and algorithm development.The way in which the specimen is mechanically and chemically processed for examination by a picture processing system is of the utmost importance. As a rule, routine methods cannot or not automatically be used. The examples Fig. 1 -Fig. 4 show results of special methods developed in our institute for karyoinetric and histoinetric measurements. 64 / SPIE Vol. 1,357 MedTech '89: Medical Imaging Fig. 1 Liver tissue showing the standard Feu lgen stain (measurement of DNA content). Downloaded From: http://proceedings.spiedigitallibrary.org/ on 06/25/2016 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspx

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“…These features include histogram features, amplitude features, texture features, etc. There is a huge body of literature dealing with measurement of these features [5,6,23,24]. Depending on the experiment or the disease under investigation, one can make use of these features to distinguish between sub-classes of the diseases.…”

Section: Disruption Of Directionalitymentioning

confidence: 99%

An Integrated System for Feature Evaluation of 3D Images of a Tissue Specimen

Adiga

2002

Analytical Cellular Pathology

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In this article we have proposed an integrated system for measurement of important features from 3D tissue images. We propose a segmentation technique, where we combine several methods to achieve a good degree of automation. Important histological and cytological three‐dimensional features and strategies to measure them are described. Figures can be viewed in colour on http://www.esacp.org/acp/2002/24‐23/adiga.htm

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Automated Image Processing for Cells and Tissue

Cited by 10 publications

References 303 publications

Long distance image transfer: First results of its use in histopathological diagnosis

Long distance image transfer: First results of its use in histopathological diagnosis

<title>Image analysis software and sample preparation demands</title>

An Integrated System for Feature Evaluation of 3D Images of a Tissue Specimen

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