title: A patch-based tensor decomposition algorithm for M-FISH image classification.
abstract: Multiplex-fluorescence in situ hybridization (M-FISH) is a chromosome imaging technique which can be used to detect chromosomal abnormalities such as translocations, deletions, duplications, and inversions. Chromosome classification from M-FISH imaging data is a key step to implement the technique. In the classified M-FISH image, each pixel in a chromosome is labeled with a class index and drawn with a pseudo-color so that geneticists can easily conduct diagnosis, for example, identifying chromosomal translocations by examining color changes between chromosomes. However, the information of pixels in a neighborhood is often overlooked by existing approaches. In this work, we assume that the pixels in a patch belong to the same class and use the patch to represent the center pixel's class information, by which we can use the correlations of neighboring pixels and the structural information across different spectral channels for the classification. On the basis of assumption, we propose a patch-based classification algorithm by using higher order singular value decomposition (HOSVD). The developed method has been tested on a comprehensive M-FISH database that we established, demonstrating improved performance. When compared with other pixel-wise M-FISH image classifiers such as fuzzy c-means clustering (FCM), adaptive fuzzy c-means clustering (AFCM), improved adaptive fuzzy c-means clustering (IAFCM), and sparse representation classification (SparseRC) methods, the proposed method gave the highest correct classification ratio (CCR), which can translate into improved diagnosis of genetic diseases and cancers. © 2016 International Society for Advancement of Cytometry.
authors.affiliation: School of Mathematical Sciences/Research Center for Image and Vision Computing, University of Electronic Science and Technology of China, Chengdu, Sichuan, 611731, China.|Department of Biomedical Engineering, Tulane University, New Orleans, Louisiana, 70118.
authors.forename: Min
authors.initials: M
authors.lastname: Wang
authors.affiliation: School of Mathematical Sciences/Research Center for Image and Vision Computing, University of Electronic Science and Technology of China, Chengdu, Sichuan, 611731, China.
authors.forename: Ting-Zhu
authors.initials: TZ
authors.lastname: Huang
authors.affiliation: Department of Biomedical Engineering, Tulane University, New Orleans, Louisiana, 70118.
authors.forename: Jingyao
authors.initials: J
authors.lastname: Li
authors.affiliation: Department of Biomedical Engineering, Tulane University, New Orleans, Louisiana, 70118.
authors.forename: Yu-Ping
authors.initials: YP
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D002869:Chromosome Aberrations / Q000145:classification; D002877:Chromosomes, Human / Q000648:ultrastructure*; D003116:Color; D016208:Databases, Factual; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D017404:In Situ Hybridization, Fluorescence / Q000379:methods*; D007621:Karyotyping / Q000379:methods*; D013194:Staining and Labeling / Q000379:methods
keywords: HOSVD; M-FISH; chromosome image classification; cytogenetics; image segmentation; tensor decomposition