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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | Abnormality Detection in Breast Images Using Deep Convolution Neural Network |
| Authors Name: | Chinu Mog Choudhari , Jhunu Debbarma , Sudeshna Das , Ankur Biswas |
| Unique Id: | IJSDR2211168 |
| Published In: | Volume 7 Issue 11, November-2022 |
| Abstract: | Breast cancer is a fast-rising disease that is occurring at a distressing degree midst the females. However, prediction of breast cancer at its initial phase may be curable and can reduce the hazard of life threats. The histopathological analysis is effective to localize and detect the malignant tumor because of its capability to analyze at cellular level. However, manual inspection followed by analysis is time taking, labor intensive and mostly have strong subjective biasness in making the accurate decision. Therefore, a CPU assisted conclusion system for estimation of the chest tumor stands out to be current field of learning. in this paper, framework design based on the applications of Convolution Neural Network for accurate prediction and classification of normal and abnormal histopathological images. The framework consists of MOBILENETV2 architecture with two output neurons to represent the normal histopathological images and another representing the abnormal histopathological images. The analysis of the framework has been carried out in publicly available BREAKHIs Benchmark Dataset. From the experimental results it is observed that framework achieved accuracy, specificity, and sensitivity of 84.83%, 81.48%, and 87.92% respectively for classification of the logical images. |
| Keywords: | Breast cancer identification, Convolutional Neural Network, Histopathological images, MOBILENETV2 |
| Cite Article: | "Abnormality Detection in Breast Images Using Deep Convolution Neural Network", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 11, page no.1116 - 1125, November-2022, Available :http://www.ijsdr.org/papers/IJSDR2211168.pdf |
| Downloads: | 000337070 |
| Publication Details: | Published Paper ID: IJSDR2211168 Registration ID:202778 Published In: Volume 7 Issue 11, November-2022 DOI (Digital Object Identifier): Page No: 1116 - 1125 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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