Lung Cancer Detection System Using based on deep learning

Lung Cancer Detection System Using based on deep learning

Registration ID: IJNRD_197207

Published ID: IJNRD2305726

DOI: Click Here to Get

Ramya C , Prof. Aruna P G , Dr. Bhagya H K

Keywords: Cancer Detection; Image processing; Feature extraction; Enhancement Watershed Masking.

Lung cancer stands as one of the most pervasive and deadliest cancer types on a global scale. Detecting lung cancer at an early stage can significantly heighten the likelihood of successful treatment and improved patient outcomes. Over the past years, image processing techniques have emerged as promising tools for facilitating early lung cancer detection. This paper presents a comprehensive review of the image processing techniques employed in lung cancer detection. The study delves into the diverse modalities of medical imaging, including X-rays, CT scans, and MRI, and explores the image processing techniques implemented for feature extraction and classification. The review accentuates the importance of employing image processing techniques for lung cancer detection, as they enable the identification of subtle changes in lung tissue that may elude the human eye. Additionally, the review emphasizes the pressing need for developing more accurate and robust image processing techniques to enhance early detection and treatment of lung cancer. In conclusion, the utilization of image processing techniques for lung cancer detection has demonstrated promise in recent times. This review sheds light on the potential benefits of leveraging these techniques to facilitate early detection and treatment of lung cancer, and highlights the importance of continued research and advancement in this field. Lung cancer is a prevalent and highly lethal form of cancer that affects populations.

Published Paper   E-Certificate

"Lung Cancer Detection System Using based on deep learning", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 5, page no.h211-h217, May-2023, Available :https://ijnrd.org/papers/IJNRD2305726.pdf

Volume 8 Issue 5, May-2023

Pages : h211-h217

Paper Reg. ID: IJNRD_197207

Published Paper Id: IJNRD2305726

Downloads: 000121115

Research Area: Engineering

Country: S.Kodagu, Karnataka, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305726.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305726

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

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

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition

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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

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