Image processing and pattern recognition algorithms for evaluation of crossed immunoelectrophoretic patterns (Crossed radioimmunoelectrophoresis analysis manager; CREAM)

Søndergaard, Ib; Poulsen, Lars K.; Hagerup, Martin; Conradsen, Knut

doi:10.1016/0003-2697(87)90286-7

Cited by 21 publications

(3 citation statements)

References 23 publications

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“…from immunoblotting of isoelectric focusmg and SDS PAGE gels. These methods can also be combined with digital image processing (22) in order to analyse and evaluate a larger number of patterns.…”

Section: Concepts In Evaluation Of Antibody Responses With Criementioning

confidence: 99%

A computational approach to the description of individual immune responses

Søndergaard

Poulsen

Osterballe

et al. 1991

Allergy

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Detailed evaluation of the IgE and IgG-subclass immune response during immunotherapy can now be performed by crossed radio immunoelectrophoresis (CRIE). Some new concepts are introduced facilitating the handling of the vast amount of data obtained by quantitating the immune response. These concepts are "distance" between antibody responses and "immune response width". The 20 patients included in this study were pollen-allergic patients who underwent specific immunotherapy in a 3-year prospective study. It was found that the immune response during immunotherapy was restricted to IgG1 and IgG4 antibodies. The semi-quantitative CRIE analysis correlated with the RAST analysis for the IgE samples before start of immunotherapy, for the IgG1 samples at week 12, and for all the IgG4 samples. During immunotherapy the number of IgG1 antibodies directed to the different antigens increased towards 11 antigens and decreased towards six. For the IgG4 antibodies the number of reactions increased towards 15 antigens and decreased towards four. The increase is generally paralleled by an increase in quantitative immune response as well. For some of the antigens a rise in the IgE antibodies is contrasted by a fall in the IgG4 antibody response, and for other antigens the opposite was true, indicating a regulatory mechanism between the IgE and the IgG4 synthesis. The IgE immune response to a number of antigens, including the major allergens before the start of immunotherapy, was quantitatively diminished during the period of immunotherapy when IgG1 was present early (week 12) in the period, and for other antigens there was a rise in IgE without an early IgG1 antibody response. This suggests that IgG1 can have a regulating influence on the IgE synthesis. Finally, we have found that IgE antibodies with specificities not present in the samples taken before immunotherapy were formed during immunotherapy. These new IgE antibodies do not, however, seem to impair the outcome of treatment.

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Section: Concepts In Evaluation Of Antibody Responses With Criementioning

confidence: 99%

A computational approach to the description of individual immune responses

Søndergaard

Poulsen

Osterballe

et al. 1991

Allergy

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“…Centralized diagnostics after image transfer may be performed based not only on visual inspection, but a central computer may also perform diagnostics more or less independently based on a computer vision algorithm. Image analysis may be performed by a remote computer [15] accessible through a network of servers [34] in much the same way as pattern recognition is applied for diverse purposes such as identification of immunoelectrophoretic patterns [35] and automated facial recognition for checking the passport at border controls [36].…”

Section: Discussionmentioning

confidence: 99%

On-Chip Imaging of Schistosoma haematobium Eggs in Urine for Diagnosis by Computer Vision

et al. 2013

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BackgroundMicroscopy, being relatively easy to perform at low cost, is the universal diagnostic method for detection of most globally important parasitic infections. As quality control is hard to maintain, misdiagnosis is common, which affects both estimates of parasite burdens and patient care. Novel techniques for high-resolution imaging and image transfer over data networks may offer solutions to these problems through provision of education, quality assurance and diagnostics. Imaging can be done directly on image sensor chips, a technique possible to exploit commercially for the development of inexpensive “mini-microscopes”. Images can be transferred for analysis both visually and by computer vision both at point-of-care and at remote locations.Methods/Principal FindingsHere we describe imaging of helminth eggs using mini-microscopes constructed from webcams and mobile phone cameras. The results show that an inexpensive webcam, stripped off its optics to allow direct application of the test sample on the exposed surface of the sensor, yields images of Schistosoma haematobium eggs, which can be identified visually. Using a highly specific image pattern recognition algorithm, 4 out of 5 eggs observed visually could be identified.Conclusions/SignificanceAs proof of concept we show that an inexpensive imaging device, such as a webcam, may be easily modified into a microscope, for the detection of helminth eggs based on on-chip imaging. Furthermore, algorithms for helminth egg detection by machine vision can be generated for automated diagnostics. The results can be exploited for constructing simple imaging devices for low-cost diagnostics of urogenital schistosomiasis and other neglected tropical infectious diseases.

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“…The possibilities of this scanning technique, based on its adaptability and flexibility, have been shown in many areas. Applications include the quantification of agglutination (Prather et al, 1986), crossed immunoelectrophoretic patterns (Sondergaard et al, 1987) and immunohistochemical images to demonstrate particular antigens (Salgaller et al, 1990;McClelland et al, 1991). In these cases, a stain (in the visual or fluorescent range) was used for quantification purposes, whereas in our case the colloidal particle itself was used to this end.…”

Section: Discussionmentioning

confidence: 99%

Colloidal carbon particles as a new label for rapid immunochemical test methods: Quantitative computer image analysis of results

Amerongen¹,

Wichers²,

Berendsen³

et al. 1993

Journal of Biotechnology

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Colloidal carbon particles can serve as label in sol particle immunoassays. The universal applicability of these particles in qualitative and (semi)quantitative immunoassays has been demonstrated. Sol particle and/or dipstick immunoassays, not yet optimized in terms of sensitivity, are discussed. The colloidal label has been used successfully in a mouse immunoglobulin isotyping kit. Human serum albumin spotted onto nitrocellulose in a concentration range of 7.8 to 1000 ng could be detected using anti-albumin antibody absorbed onto colloidal carbon particles. It was also possible to perform a competitive assay with this conjugate for a concentration range of free human serum albumin varying from 0.25 to 6.75 micrograms. The Kunitz-type trypsin inhibitor from soybean was determined by a colloidal carbon based immunoassay in a range of 2.5 to 160 ng. In this assay, free and colloidal carbon-bound inhibitor competed for binding specific antibodies spotted onto a nitrocellulose membrane. An image- and data-processing procedure has been developed that enables a rapid and simple quantification of colloidal carbon sol particle immunoassays. The average grey level of a spot is taken as a measure for quantitative purposes. This so-called Sol-particle Image Processed ImmunoAssay (SIPIA) procedure is equally well applicable to assays using other colloidal particles.

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Image processing and pattern recognition algorithms for evaluation of crossed immunoelectrophoretic patterns (Crossed radioimmunoelectrophoresis analysis manager; CREAM)

Cited by 21 publications

References 23 publications

A computational approach to the description of individual immune responses

A computational approach to the description of individual immune responses

On-Chip Imaging of Schistosoma haematobium Eggs in Urine for Diagnosis by Computer Vision

Colloidal carbon particles as a new label for rapid immunochemical test methods: Quantitative computer image analysis of results

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