ARTIFICIAL NEURAL NETWORKS IN IMAGE PROCESSING FOR EARLY DETECTION OF BREAST CANCER.

ARTIFICIAL NEURAL NETWORKS IN IMAGE PROCESSING FOR EARLY DETECTION OF BREAST CANCER.

Registration ID: IJNRD_186583

Published ID: IJNRD2302002

DOI: Click Here to Get

Santhosh Bharadwaj M N , Thanuja D , Sinchana S

Artificial neural networks (ANNs) have been widely used in image processing for various applications, including early detection of breast cancer. One of the main advantages of using ANNs for early detection of breast cancer is their ability to learn from data. ANNs can be trained on large sets of data and can learn to detect patterns in images that are not visible to the human eye. This ability to learn from data can help to improve the accuracy of early detection of breast cancer, which is crucial for the successful treatment of this disease. The current state of research in this field is promising. Many studies have shown that ANNs can be used to improve the accuracy of early detection of breast cancer. However, more research is needed to further improve the accuracy of ANNs and to address the challenges mentioned above. The purpose of this review is to analyse the contents of recently published literature with special attention to techniques and states of the art of NN in medical imaging.

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"ARTIFICIAL NEURAL NETWORKS IN IMAGE PROCESSING FOR EARLY DETECTION OF BREAST CANCER.", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 2, page no.a7-a15, February-2023, Available :https://ijnrd.org/papers/IJNRD2302002.pdf

Volume 8 Issue 2, February-2023

Pages : a7-a15

Paper Reg. ID: IJNRD_186583

Published Paper Id: IJNRD2302002

Downloads: 000121129

Research Area: Science & Technology

Country: Bangalore, Karnataka, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2302002.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2302002

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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