Semi-automated image analysis of gel electrophoresis of cerebrospinal fluid for oligoclonal band detection
Résumé
Detection of oligoclonal electrophoretic bands in cerebrospinal fluid (CSF) is an important diagnostic tool for Multiple Sclerosis (MS). Electrophoretic profiles are difficult to interpret due to low contrast and artefacts. A semi-automated method to ease analysis and to reduce subjectivity is presented. The method sequentially converts color images to grayscale, realigns bands, removes artifacts, then converts 2D images to a signal, before detecting, thresholding and editing peaks to optimize profiles. Such treated profiles (21 positive and 15 negative) are compared to ground truth analysis of an expert biologist. 16 profiles over 21 are well detected positive and 12 profiles over 15 are detected negative, results seem similar to inter-experts variability reported in literature.
Mots clés
Gray-scale
Immune system
Fluids
Image color analysis
DNA
biomedical optical imaging
brain
electrophoresis
image colour analysis
medical image processing
neurophysiology
optimisation
semiautomated image analysis
gel electrophoresis
cerebrospinal fluid
oligoclonal electrophoretic band detection
diagnostic tool
electrophoretic profiles
color images
grayscale
artifact removal
band realignment
2D images
profile optimization
ground truth analysis
interexperts variability
Distortion
Biomembranes