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Hyperspectral imaging in medicine: image pre-processing problems and solutions in Matlab.

Robert Koprowski¹

¹Department of Biomedical Computer Systems, University of Silesia, Faculty of Computer Science and Materials Science, Institute of Computer Science, ul. Będzińska 39, Sosnowiec, 41-200, Poland. robert.koprow@us.edu.pl.

Journal of Biophotonics

|February 14, 2015

Summary

This paper introduces new, license-free Matlab methods for hyperspectral image pre-processing and analysis, addressing common issues encountered with this data type.

Keywords:

ENVI Matlab Specim biomedical hyperspectral image processing medical image mirror scanner

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Area of Science:

Remote Sensing
Image Processing
Data Analysis

Background:

Hyperspectral imaging generates complex, high-dimensional data.
Pre-processing is crucial for accurate analysis of hyperspectral images.
Existing software tools may present limitations or licensing costs.

Purpose of the Study:

To present solutions for common hyperspectral image pre-processing challenges.
To introduce novel, accessible methods for preliminary analysis.
To provide open-source Matlab code for practical application.

Main Methods:

Development of new algorithms for hyperspectral image pre-processing.
Implementation of these methods in Matlab.
Demonstration of analysis with sample results.

Main Results:

Successfully addressed pre-processing problems in Matlab.
Developed and presented new, license-free Matlab source code.
Showcased practical hyperspectral image analysis with sample outputs.

Conclusions:

The proposed methods offer effective and accessible solutions for hyperspectral image pre-processing.
The open-source Matlab code facilitates wider adoption and research.
The study demonstrates the utility of the new methods for practical analysis.