Enhancing Multispectral Breast Imaging Quality Through Frame Accumulation and Hybrid GA-CPSO Registration

Multispectral transmission imaging has emerged as a promising technique for imaging breast tissue with high resolution. However, the method encounters challenges such as low grayscale, noisy transmission images with weak signals, primarily due to the strong absorption and scattering of light in brea...

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Main Authors: Tsabeeh Salah M. Mahmoud, Adnan Munawar, Muhammad Zeeshan Nawaz, Yuanyuan Chen
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Bioengineering
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Online Access:https://www.mdpi.com/2306-5354/11/12/1281
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author Tsabeeh Salah M. Mahmoud
Adnan Munawar
Muhammad Zeeshan Nawaz
Yuanyuan Chen
author_facet Tsabeeh Salah M. Mahmoud
Adnan Munawar
Muhammad Zeeshan Nawaz
Yuanyuan Chen
author_sort Tsabeeh Salah M. Mahmoud
collection DOAJ
description Multispectral transmission imaging has emerged as a promising technique for imaging breast tissue with high resolution. However, the method encounters challenges such as low grayscale, noisy transmission images with weak signals, primarily due to the strong absorption and scattering of light in breast tissue. A common approach to improve the signal-to-noise ratio (SNR) and overall image quality is frame accumulation. However, factors such as camera jitter and respiratory motion during image acquisition can cause frame misalignment, degrading the quality of the accumulated image. To address these issues, this study proposes a novel image registration method. A hybrid approach combining a genetic algorithm (GA) and a constriction factor-based particle swarm optimization (CPSO), referred to as GA-CPSO, is applied for image registration before frame accumulation. The efficiency of this hybrid method is enhanced by incorporating a squared constriction factor (SCF), which speeds up the registration process and improves convergence towards optimal solutions. The GA identifies potential solutions, which are then refined by CPSO to expedite convergence. This methodology was validated on the sequence of breast frames taken at 600 nm, 620 nm, 670 nm, and 760 nm wavelength of light and proved the enhancement of accuracy by various mathematical assessments. It demonstrated high accuracy (99.93%) and reduced registration time. As a result, the GA-CPSO approach significantly improves the effectiveness of frame accumulation and enhances overall image quality. This study explored the groundwork for precise multispectral transmission image segmentation and classification.
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spelling doaj-art-20811de5423646c497f86ba42de97d9c2024-12-27T14:11:43ZengMDPI AGBioengineering2306-53542024-12-011112128110.3390/bioengineering11121281Enhancing Multispectral Breast Imaging Quality Through Frame Accumulation and Hybrid GA-CPSO RegistrationTsabeeh Salah M. Mahmoud0Adnan Munawar1Muhammad Zeeshan Nawaz2Yuanyuan Chen3Medical School, Faculty of Medicine, Tianjin University, Tianjin 300072, ChinaMedical School, Faculty of Medicine, Tianjin University, Tianjin 300072, ChinaMedical School, Faculty of Medicine, Tianjin University, Tianjin 300072, ChinaMedical School, Faculty of Medicine, Tianjin University, Tianjin 300072, ChinaMultispectral transmission imaging has emerged as a promising technique for imaging breast tissue with high resolution. However, the method encounters challenges such as low grayscale, noisy transmission images with weak signals, primarily due to the strong absorption and scattering of light in breast tissue. A common approach to improve the signal-to-noise ratio (SNR) and overall image quality is frame accumulation. However, factors such as camera jitter and respiratory motion during image acquisition can cause frame misalignment, degrading the quality of the accumulated image. To address these issues, this study proposes a novel image registration method. A hybrid approach combining a genetic algorithm (GA) and a constriction factor-based particle swarm optimization (CPSO), referred to as GA-CPSO, is applied for image registration before frame accumulation. The efficiency of this hybrid method is enhanced by incorporating a squared constriction factor (SCF), which speeds up the registration process and improves convergence towards optimal solutions. The GA identifies potential solutions, which are then refined by CPSO to expedite convergence. This methodology was validated on the sequence of breast frames taken at 600 nm, 620 nm, 670 nm, and 760 nm wavelength of light and proved the enhancement of accuracy by various mathematical assessments. It demonstrated high accuracy (99.93%) and reduced registration time. As a result, the GA-CPSO approach significantly improves the effectiveness of frame accumulation and enhances overall image quality. This study explored the groundwork for precise multispectral transmission image segmentation and classification.https://www.mdpi.com/2306-5354/11/12/1281breast cancermultispectral transmission imagingframe accumulationimage registrationconstriction factorparticle swarm optimization
spellingShingle Tsabeeh Salah M. Mahmoud
Adnan Munawar
Muhammad Zeeshan Nawaz
Yuanyuan Chen
Enhancing Multispectral Breast Imaging Quality Through Frame Accumulation and Hybrid GA-CPSO Registration
Bioengineering
breast cancer
multispectral transmission imaging
frame accumulation
image registration
constriction factor
particle swarm optimization
title Enhancing Multispectral Breast Imaging Quality Through Frame Accumulation and Hybrid GA-CPSO Registration
title_full Enhancing Multispectral Breast Imaging Quality Through Frame Accumulation and Hybrid GA-CPSO Registration
title_fullStr Enhancing Multispectral Breast Imaging Quality Through Frame Accumulation and Hybrid GA-CPSO Registration
title_full_unstemmed Enhancing Multispectral Breast Imaging Quality Through Frame Accumulation and Hybrid GA-CPSO Registration
title_short Enhancing Multispectral Breast Imaging Quality Through Frame Accumulation and Hybrid GA-CPSO Registration
title_sort enhancing multispectral breast imaging quality through frame accumulation and hybrid ga cpso registration
topic breast cancer
multispectral transmission imaging
frame accumulation
image registration
constriction factor
particle swarm optimization
url https://www.mdpi.com/2306-5354/11/12/1281
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AT adnanmunawar enhancingmultispectralbreastimagingqualitythroughframeaccumulationandhybridgacpsoregistration
AT muhammadzeeshannawaz enhancingmultispectralbreastimagingqualitythroughframeaccumulationandhybridgacpsoregistration
AT yuanyuanchen enhancingmultispectralbreastimagingqualitythroughframeaccumulationandhybridgacpsoregistration