Exploring Band Selection Methods for Enhanced Chromosomal Analysis in Hyperspectral Imaging

Chromosome characterization is crucial in cytogenetic research and diagnostics, necessitating precise imaging methods to ensure proper analyses. The aim of this project is to identify a reliable method for chromosomal characterization that uses hyperspectral imagery of stained metaphase chromosomes using bright-field microscopy. We analyzed four hyperspectral images of stained chromosomes acquired under bright-field illumination. To address the high dimensionality of the hyperspectral hypercubes, we applied five dimension reduction algorithms based on spectral band selection to determine the most effective approach. A comparative study was conducted between five band selection methods to assess their effectiveness in chromosome characterization. The results indicate that sparse subspace clustering and multi-objective band selection are the most effective methods, outperforming the others in reducing the spectral dimensionality of the hyperspectral data, while preserving key properties essential for accurate chromosomes characterization. This study demonstrates that careful selection of spectral bands can enhance the analysis of spectral hypercubes for chromosome characterization.

Authors

Institutions

Publication Details

Journal
Applied Spectroscopy
Published
2025-11-21
DOI
https://doi.org/10.1177/00037028251403574
Citations
1
Primary Topic
Genomic variations and chromosomal abnormalities
Type
article
Field-Weighted Citation Impact
1.82
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring Band Selection Methods for Enhanced Chromosomal Analysis in Hyperspectral Imaging

Nathalie Douet‐Guilbert, Jean-Marie Guyader, Mohammed El Amine BECHAR, Nesma Settouti et al.
1 citations
Applied Spectroscopy
Genomic variations and chromosomal abnormalities
1.82
article

Exploring Band Selection Methods for Enhanced Chromosomal Analysis in Hyperspectral Imaging

Nathalie Douet‐Guilbert, Jean-Marie Guyader, Mohammed El Amine BECHAR, Nesma Settouti, Marwa El Bouz, Najoua ZEFFATE, Marie-BÃl’rengÃĺre TROADEC
article en
1 citations

Abstract

Chromosome characterization is crucial in cytogenetic research and diagnostics, necessitating precise imaging methods to ensure proper analyses. The aim of this project is to identify a reliable method for chromosomal characterization that uses hyperspectral imagery of stained metaphase chromosomes using bright-field microscopy. We analyzed four hyperspectral images of stained chromosomes acquired under bright-field illumination. To address the high dimensionality of the hyperspectral hypercubes, we applied five dimension reduction algorithms based on spectral band selection to determine the most effective approach. A comparative study was conducted between five band selection methods to assess their effectiveness in chromosome characterization. The results indicate that sparse subspace clustering and multi-objective band selection are the most effective methods, outperforming the others in reducing the spectral dimensionality of the hyperspectral data, while preserving key properties essential for accurate chromosomes characterization. This study demonstrates that careful selection of spectral bands can enhance the analysis of spectral hypercubes for chromosome characterization.

Applied SpectroscopyVol. 80(2)
Inserm (FR), Institut Supérieur de l'Électronique et du Numérique (FR), Centre Hospitalier Régional Universitaire de Brest (FR)
Openalex Percentile: Top 11%
Genomic variations and chromosomal abnormalities
1.82
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.