Pixel-by-pixel classification of MFISH images
Mehul Sampat,Kenneth R. Castleman,Alan C. Bovik +2 more
- Vol. 2, pp 999-1000
Reads0
Chats0
TLDR
An automatic pixel by pixel classification algorithm for M-FISH images using a Bayes classifier was proposed and an overall classification accuracy of 95% was obtained.Abstract:
Multiplex Fluorescence In-Situ Hybridization (M-FISH) is a recently developed chromosome imaging method in which each chromosome is labelled with 5 fluors (dyes) and is also counterstained with DAPI. This paper proposes an automatic pixel by pixel classification algorithm for M-FISH images using a Bayes classifier. The M-FISH pixel classification was approached as a 25 class 6 feature pattern recognition problem. The classifier was trained and tested on non-overlapping data sets and an overall classification accuracy of 95% was obtained.read more
Citations
More filters
Journal ArticleDOI
Segmentation of M-FISH Images for Improved Classification of Chromosomes With an Adaptive Fuzzy C-means Clustering Algorithm
TL;DR: An adaptive fuzzy c-means algorithm was developed and applied to the segmentation and classification of multicolor fluorescence in situ hybridization (M-FISH) images, which can be used to detect chromosomal abnormalities for cancer and genetic disease diagnosis.
Journal ArticleDOI
Maximum-likelihood techniques for joint segmentation-classification of multispectral chromosome images
TL;DR: It is shown that the proposed multispectral joint segmentation-classification method outperforms past grayscale segmentation methods when decomposing touching chromosomes and can also be used as a reliable indicator of errors in segmentation, errors in classification, and chromosome anomalies.
Journal ArticleDOI
A Multichannel Watershed-Based Segmentation Method for Multispectral Chromosome Classification
TL;DR: The combination of the multichannel segmentation and the region-based classification is found to improve the overall classification accuracy compared to pixel-by-pixel approaches.
Proceedings ArticleDOI
A watershed based segmentation method for multispectral chromosome images classification.
TL;DR: An automated method for chromosome classification in M-FISH images is presented and by introducing feature averaging on watershed basins, the proposed technique achieves substantially better results than previous methods at a lower computational cost.
Journal ArticleDOI
A survey of neural network based automated systems for human chromosome classification
Faroudja Abid,Latifa Hamami +1 more
TL;DR: A comprehensive review of past and recent research in the area of automatic chromosome classification systems is provided, starting by reviewing methods for feature extraction, followed by a neural network based chromosome classifiers survey.
References
More filters
Journal ArticleDOI
Karyotyping human chromosomes by combinatorial multi-fluor FISH
TL;DR: The data suggest that multiplex-fluorescence in situ hybridization (M-FISH) could have wide clinical utility and complement standard cytogenetics, particularly for the characterization of complex karyotypes.
Journal ArticleDOI
FISH image analysis
TL;DR: The techniques described here, and similar ones, will become a routine part of research and clinical practice as the use of FISH techniques expand and one can expect digital image processing to become an indispensable part of the activity.
Proceedings ArticleDOI
Minimum entropy segmentation applied to multi-spectral chromosome images
TL;DR: A segmentation algorithm is proposed for M-FISH images that minimizes the entropy of classified pixels within possible chromosomes and is shown to correctly decompose even difficult clusters of touching and overlapping chromosomes.