A Study of Deep Convolutional Neural Network for Diagnosing Breast Cancer in Thermographic Images

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GHOLIZADEH MOHAMMAD HOSSEIN; GHAYOUMI ZADEH HOSSEIN; FATEHI MARJ HASAN; AHMADINEJAD NASRIN

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Journal: Jundishapur Scientific Medical Journal Year:2019 | Volume:18 | Issue:6 Page(s): 615-629

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Title

A Study of Deep Convolutional Neural Network for Diagnosing Breast Cancer in Thermographic Images

Author(s)

GHOLIZADEH MOHAMMAD HOSSEIN | GHAYOUMI ZADEH HOSSEIN | FATEHI MARJ HASAN | AHMADINEJAD NASRIN | Issue Writer Certificate

Keywords

Breast CancerQ2

Thermal ImagesQ1

Deep Neural NetworkQ1

ClassificationQ1

Abstract

Background and Objectives: Computer-aided design diagnostic systems are widely used in the differential diagnosis of Breast Cancer. Therefore, improving the accuracy of a CAD system has become an important field of research. In this study, we investigated CAD systems based on Deep Neural Networks of convolution type to detect Breast Cancer in thermographic images. Subjects and Methods: For analyzing the proposed model, the Database for Mastology Research (DMR) database was used. The number of the participants examined were 196, including 41 cases of cancer and 155 healthy subjects. Each person had 10 images of thermography. The total number of the analyzed images included 1960 images of thermography. The Classification of Thermal Images including cancerous and healthy images is based on three types of deep convolution neural networks including google net, resnet18 and vgg16. Results: The accuracy and specificity of the results using a neural network models of deep pre-training on google-net, resnet18 and vgg16 was 85. 03%-89. 7%, 83. 8%-91. 9% and 85. 03%-91, 01% respectively. The proposed model is capable of providing a significant response to the different breast tissue morphologies. Conclusion: The model of deep artificial neural network can be used as an efficient and intelligent way to detect cancer in original Thermal Images without extracting features. However, more studies are needed to design other models of artificial neural networks based on deep learning for detection of malignant or benign cancers in thermal imagery.

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APA: Copy

GHOLIZADEH, MOHAMMAD HOSSEIN, GHAYOUMI ZADEH, HOSSEIN, FATEHI MARJ, HASAN, & AHMADINEJAD, NASRIN. (2019). A Study of Deep Convolutional Neural Network for Diagnosing Breast Cancer in Thermographic Images. JUNDISHAPUR SCIENTIFIC MEDICAL JOURNAL, 18(6 ), 615-629. SID. https://sid.ir/paper/364915/en

Vancouver: Copy

GHOLIZADEH MOHAMMAD HOSSEIN, GHAYOUMI ZADEH HOSSEIN, FATEHI MARJ HASAN, AHMADINEJAD NASRIN. A Study of Deep Convolutional Neural Network for Diagnosing Breast Cancer in Thermographic Images. JUNDISHAPUR SCIENTIFIC MEDICAL JOURNAL[Internet]. 2019;18(6 ):615-629. Available from: https://sid.ir/paper/364915/en

IEEE: Copy

MOHAMMAD HOSSEIN GHOLIZADEH, HOSSEIN GHAYOUMI ZADEH, HASAN FATEHI MARJ, and NASRIN AHMADINEJAD, “A Study of Deep Convolutional Neural Network for Diagnosing Breast Cancer in Thermographic Images,” JUNDISHAPUR SCIENTIFIC MEDICAL JOURNAL, vol. 18, no. 6 , pp. 615–629, 2019, [Online]. Available: https://sid.ir/paper/364915/en

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