Evaluation of semi-automatic image analysis tools for cerebrospinal fluid electrophoresis of IgG oligoclonal bands

Forzy, G.; Peyrodie, Laurent; Boudet, Samuel; Wang, Z.; Vinclair, A.; Chieux, Vincent

doi:10.1016/j.plabm.2017.11.001

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…The synthetic lane background was generated by randomly choosing one of five real negative grayscale profiles (i.e., profiles without OCBs) filtered beforehand with a two-dimensional (2D) Gaussian filter. Gaussian functions are commonly used in the literature to approximate band shapes [ 10 , 18 ] hence, the bands were created using a Gaussian density function. The expected value was the band position, and the standard deviation (SD) was proportional to the band width (band width

.…”

Section: Methodsmentioning

confidence: 99%

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Oligoclonal Band Straightening Based on Optimized Hierarchical Warping for Multiple Sclerosis Diagnosis

Haddad

Boudet

Peyrodie

et al. 2022

Sensors

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The detection of immunoglobulin G (IgG) oligoclonal bands (OCB) in cerebrospinal fluid (CSF) by isoelectric focusing (IEF) is a valuable tool for the diagnosis of multiple sclerosis. Over the last decade, the results of our clinical research have suggested that tears are a non-invasive alternative to CSF. However, since tear samples have a lower IgG concentration than CSF, a sensitive OCB detection is therefore required. We are developing the first automatic tool for IEF analysis, with a view to speeding up the current visual inspection method, removing user variability, reducing misinterpretation, and facilitating OCB quantification and follow-up studies. The removal of band distortion is a key image enhancement step in increasing the reliability of automatic OCB detection. Here, we describe a novel, fully automatic band-straightening algorithm. The algorithm is based on a correlation directional warping function, estimated using an energy minimization procedure. The approach was optimized via an innovative coupling of a hierarchy of image resolutions to a hierarchy of transformation, in which band misalignment is corrected at successively finer scales. The algorithm’s performance was assessed in terms of the bands’ standard deviation before and after straightening, using a synthetic dataset and a set of 200 lanes of CSF, tear, serum and control samples on which experts had manually delineated the bands. The number of distorted bands was divided by almost 16 for the synthetic lanes and by 7 for the test dataset of real lanes. This method can be applied effectively to different sample types. It can realign minimal contrast bands and is robust for non-uniform deformations.

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.…”

Section: Methodsmentioning

confidence: 99%

“…We are currently developing the first automatic tool for OCB detection in CSF and tear samples [ 9 , 10 , 11 ]. Our objective is to provide an easy-to-use solution with a reasonable processing time, to ensure its adoption by hospital physicians.…”

Section: Introductionmentioning

confidence: 99%

Oligoclonal Band Straightening Based on Optimized Hierarchical Warping for Multiple Sclerosis Diagnosis

Haddad

Boudet

Peyrodie

et al. 2022

Sensors

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Toward an automatic tool for oligoclonal band detection in cerebrospinal fluid and tears for multiple sclerosis diagnosis: lane segmentation based on a ribbon univariate open active contour

Haddad

Boudet

Peyrodie

et al. 2020

Med Biol Eng Comput

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Fuzzy clustering discrete equilibrium analysis on the promotion of government venture investment to enterprise innovation

Feng

2020

IFS

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In order to effectively improve the accuracy of related analysis models in the application of government risk investment, a government risk investment prediction model based on fuzzy clustering discrete algorithm is put forward in this paper. First of all, government risk investment problem is analyzed. Based on Markowitz theory, the general government risk investment model is considered, and the market value constraint and the upper bound constraint are combined to improve the government risk investment model and obtain the mixed constraint government risk investment model. Secondly, the fuzzy clustering discrete algorithm is introduced in the analysis process of government venture investment model, and it is used to solve the mixed constraint analysis model of government venture investment. In addition, to further improve the performance of discrete algorithm based on fuzzy clustering in the model solving process, automatic contraction and expansion of factors is used to carry out adaptive learning of related parameters based fuzzy clustering discrete algorithm, and improve the convergence of the algorithm. Finally, the simulation experiments on some stock samples of investment sector show that the algorithm in this paper can obtain more ideal government venture investment schemes, so as to reduce investment risk and obtain greater investment returns.

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Evaluation of semi-automatic image analysis tools for cerebrospinal fluid electrophoresis of IgG oligoclonal bands

Cited by 3 publications

References 16 publications

Oligoclonal Band Straightening Based on Optimized Hierarchical Warping for Multiple Sclerosis Diagnosis

Oligoclonal Band Straightening Based on Optimized Hierarchical Warping for Multiple Sclerosis Diagnosis

Toward an automatic tool for oligoclonal band detection in cerebrospinal fluid and tears for multiple sclerosis diagnosis: lane segmentation based on a ribbon univariate open active contour

Fuzzy clustering discrete equilibrium analysis on the promotion of government venture investment to enterprise innovation

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