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  Published Paper Details:

  Paper Title

A REVIEW ON BREAST CANCER DETECTION APPROACHES FOR VARIOUS IMAGE DATA SETS

  Authors

  Mr. Gurusiddayya Hiremath,  Dr. Jose Alex Mathew

  Keywords

Cancer, Breast Cancer, Machine Learning, Mammogram, Histopathology image, Pre-Processing, Segmentation

  Abstract


According to global statistics, deaths among women due to breast cancer (BC) are the leading cause out of all the several types of cancers. Hence treating breast cancer as early as possible, and even relatively complicated to detect and analyse at the beginning stage. The conventional method is time-consuming and not efficient and very less accurate. Henceforth an efficient technique to diagnose the cancerous cell, not including human association close to accuracy. CT scan is a particular case of Mammography, which adopts the X-ray technique & uses superior-resolution pictures such that, it perceives fine tumors in the breast. The review paper elaborates on the recognition of the BC by employing various image processing (IP) application and techniques

  IJCRT's Publication Details

  Unique Identification Number - IJCRTT020011

  Paper ID - 223637

  Page Number(s) - 40-44

  Pubished in - Volume 10 | Issue 8 | August 2022

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Mr. Gurusiddayya Hiremath,  Dr. Jose Alex Mathew,   "A REVIEW ON BREAST CANCER DETECTION APPROACHES FOR VARIOUS IMAGE DATA SETS", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.10, Issue 8, pp.40-44, August 2022, Available at :http://www.ijcrt.org/papers/IJCRTT020011.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


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ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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