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IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

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IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...
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There are two main infrared (IR) spectrophotometers: dispersive IR spectrometers and Fourier transform infrared (FTIR) spectrometers. In a dispersive IR spectrometer, a beam of infrared radiation produced by a hot wire is divided into two parallel equal-intensity beams using mirrors. One beam passes through the sample, while another is a reference beam. The beams then move through the monochromator, which separates the radiations into a continuous spectrum of different frequencies. The...
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When electromagnetic radiation passes through a material, atoms or molecules transition from a lower to a higher energy state by absorbing radiation corresponding to the energy difference between the two states. The absorption of infrared (IR) radiation causes transitions between vibrational energy levels in a molecule. Therefore, IR spectroscopy is a useful analytical tool for determining the molecular structure of molecules.
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IR Spectrum01:19

IR Spectrum

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When infrared (IR) radiation passes through a molecule, the bonds stretch or bend by absorbing the radiation. This absorption creates the molecule's absorption spectrum, which is the plot of its percentage transmittance versus wavenumber.
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IR Spectroscopy: Molecular Vibration Overview01:24

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When Infrared (IR) radiation passes through a covalently bonded molecule, the bonds transition from lower to higher vibrational levels. The fundamental vibrational motions that result in infrared absorption can be classified as stretching or bending vibrations.
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In IR spectroscopy, signals produced by the X−H bonds (such as C−H, O−H, or N−H) can be observed in the frequency range of  2700–4000 cm–1. The C−H stretching vibration forms sharp bands in the region 2850–3000 cm–1. The presence of the O−H stretching vibration leads to the forming of an absorption band in the frequency range 3650–3200 cm−1. At the same time, N−H stretching can be confirmed by absorption bands in...
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High-definition Fourier Transform Infrared FT-IR Spectroscopic Imaging of Human Tissue Sections towards Improving Pathology
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Fourier transform infrared spectroscopy microscopic imaging classification based on multifractal methods.

Lian Liu, Xiukun Yang, Xiaojun Jing

    Applied Optics
    |February 25, 2017
    PubMed
    Summary
    This summary is machine-generated.

    A novel multifractal analysis (MFA) method using neighborhood spatial correlation (NSC) effectively identifies cholesterol in rabbit arteries. This spatial-spectral approach enhances accuracy and reduces noise in Fourier transform infrared spectroscopy imaging.

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    Area of Science:

    • Biomedical Engineering
    • Spectroscopy
    • Image Analysis

    Background:

    • Multifractal analysis (MFA) is utilized for complex biological tissue structures.
    • Fourier transform infrared spectroscopy (FTIR) microscopic imaging provides detailed tissue information.
    • Differentiating tissue components like cholesterol requires advanced feature extraction methods.

    Purpose of the Study:

    • To propose a new multifractal analysis (MFA) methodology using neighborhood spatial correlation (NSC) for texture feature extraction.
    • To combine spatial features from NSC with spectral features from characteristic absorption peaks (CAPs) for enhanced information.
    • To differentiate cholesterol in rabbit artery FTIR microscopic images using a spatial-spectral feature set.

    Main Methods:

    • Developed a new MFA methodology based on neighborhood spatial correlation (NSC) for texture analysis.
    • Integrated spatial features (NSC) with spectral features (CAPs) into a spatial-spectral structure.
    • Employed a support vector machine (SVM) classifier on FTIR microscopic imaging data of rabbit arteries (4000-720 cm⁻¹).

    Main Results:

    • The proposed spatial-spectral feature structure achieved higher accuracy in differentiating cholesterol compared to PCA and 2DPCA.
    • The NSC method demonstrated effectiveness in reducing speckle noise compared to other interface and variance methods.
    • The convergence rate of the weight factor q was not adversely affected by the NSC method.

    Conclusions:

    • The novel spatial-spectral feature extraction method based on MFA and NSC offers a robust approach for tissue analysis.
    • This method enhances the accuracy of cholesterol detection in biological tissues using FTIR microscopy.
    • The NSC technique provides a significant advantage in noise reduction for spectroscopic imaging applications.