Breast Cancer Detection Using Infrared Thermal Imaging and a Deep Learning Model

Sensors
Sebastien Jean MambouKamil Kuca

Abstract

Women's breasts are susceptible to developing cancer; this is supported by a recent study from 2016 showing that 2.8 million women worldwide had already been diagnosed with breast cancer that year. The medical care of a patient with breast cancer is costly and, given the cost and value of the preservation of the health of the citizen, the prevention of breast cancer has become a priority in public health. Over the past 20 years several techniques have been proposed for this purpose, such as mammography, which is frequently used for breast cancer diagnosis. However, false positives of mammography can occur in which the patient is diagnosed positive by another technique. Additionally, the potential side effects of using mammography may encourage patients and physicians to look for other diagnostic techniques. Our review of the literature first explored infrared digital imaging, which assumes that a basic thermal comparison between a healthy breast and a breast with cancer always shows an increase in thermal activity in the precancerous tissues and the areas surrounding developing breast cancer. Furthermore, through our research, we realized that a Computer-Aided Diagnostic (CAD) undertaken through infrared image processing could ...Continue Reading

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Citations

Aug 6, 2019·Annals of Saudi Medicine·Khawaja Bilal WaheedZechriah Jebakumar Arulanatham
Jul 3, 2020·Journal of Medical Systems·Aayesha Hakim, R N Awale
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Oct 7, 2021·Dento Maxillo Facial Radiology·Elisa Diniz de LimaDaniela Pita Melo

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Methods Mentioned

BETA
fluorescence imaging
biopsy
feature extraction

Software Mentioned

ConvNet
LinearSVC
No Touch

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