Thermogram Adaptive Efficient Model for Breast Cancer Detection Using Fractional Derivative Mask and Hybrid Feature Set in the IoT Environment

Ritam Sharma; JankiBallabh Sharma; Ranjan Maheshwari; Praveen Agarwal

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Thermogram Adaptive Efficient Model for Breast Cancer Detection Using Fractional Derivative Mask and Hybrid Feature Set in the IoT Environment

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In this paper,a novel hybrid texture feature set and fractional derivative filter-based breast cancer detection model is introduced.This paper also introduces the application of a histogram of linear bipolar pattern features(HLBP)for breast thermogram classification.Initially,breast tissues are separated by masking operation and filtered by Gr¨umwald–Letnikov fractional derivative-based Sobel mask to enhance the texture and rectify the noise.A novel hybrid feature set usingHLBP and other statistical feature sets is derived and reduced by principal component analysis.Radial basis function kernel-based support vector machine is employed for detecting the abnormality in the thermogram.The performance parameters are calculated using five-fold cross-validation scheme using MATLAB 2015a simulation software.The proposedmodel achieves the classification accuracy,sensitivity,specificity,and area under the curve of 94.44%,95.55%,92.22%,96.11%,respectively.A comparative investigation of different texture features with respect to fractional orderαto classify the breast malignancy is also presented.The proposed model is also compared with a few existing state-of-art schemes which verifies the efficacy of the model.Fractional orderαoffers extra adaptability in overcoming the limitations of thermal imaging techniques and assists radiologists in prior breast cancer detection.The proposed model is more generalized which can be used with different thermal image acquisition protocols and IoT based applications.

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《工程与科学中的计算机建模（英文）》 |2022年第2期|923-947|共25页
作者
Ritam Sharma; JankiBallabh Sharma; Ranjan Maheshwari; Praveen Agarwal;
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作者单位

Rajasthan Technical University;

Anand International College of Engineering;

Nonlinear Dynamics Research Center(NDRC) University Arab Emirates;

International Center for Basic and Applied Sciences;

Institute of MathematicalModeling;

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原文格式 PDF
正文语种 chi
中图分类肿瘤学;
关键词
Thermal image; breast cancer; fractional derivative mask; image texture analysis; feature extraction; radial basis function; machine learning;

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Thermogram Adaptive Efficient Model for Breast Cancer Detection Using Fractional Derivative Mask and Hybrid Feature Set in the IoT Environment

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