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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 10
Issue Published : 115
Article Submitted : 19456
Article Published : 8041
Total Authors : 21252
Total Reviewer : 769
Total Countries : 144
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| Paper Title: | Detection and Classification of Breast Cancer using Thermograms |
| Authors Name: | Preksha A Das , Supritha S , S.Y.Pattar |
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| Author Reg. ID: |
IJRTI_185255
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| Published Paper Id: | IJRTI2302041 |
| Published In: | Volume 8 Issue 2, February-2023 |
| DOI: | |
| Abstract: | Breast cancer is the second most common cancer in the world. Early diagnosis and treatment increase the patient’s chances of healing. The temperature of cancerous tissues is generally higher than that of healthy neighboring tissues, making thermography an option to be considered in screening strategies for this type of cancer. In this, we propose a computational method for breast - thermography image analysis for screening patients with abnormalities in the breast. Automated diagnostic tools always provide the doctors with the very valuable second opinion during disease diagnosis. This paper discusses an automated approach for breast cancer detection using Thermal Infrared (TIR) images. Images are extracted from the temperature matrix, dataset available at DMR visual labs and Kaggle website the texture features based on different grey levels are extracted. There are a series of texture features that play a vital role in asymmetry analysis of breast thermograms. This paper mainly emphasizes on investigating those statistical features, which can adequately differentiate the healthy breast thermograms from pathological breast thermograms. |
| Keywords: | Breast thermal images, Statistical features. Screening strategies, Diagnosis. |
| Cite Article: | "Detection and Classification of Breast Cancer using Thermograms", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 2, page no.242 - 245, February-2023, Available :http://www.ijrti.org/papers/IJRTI2302041.pdf |
| Downloads: | 000205157 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2302041
Registration ID:185255
Published In: Volume 8 Issue 2, February-2023
DOI (Digital Object Identifier):
Page No: 242 - 245 Country: Bangalore, Karnataka, India Research Area: Bio Medical Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2302041 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2302041 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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