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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (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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| Paper Title: | A semi automatic classification of Lung disease using CNN |
| Authors Name: | KRISHNAVENI T , PRABADEVI P |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJNRD_188168
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| Published Paper Id: | IJNRD2303028 |
| Published In: | Volume 8 Issue 3, March-2023 |
| DOI: | |
| Abstract: | CT images were used to identify the lung disease. It is used to observe a variety of lung texture patterns. These images are a mixture of different patterns and therefore it becomes very difficult for the radiologist to distinguish between them and diagnose the disease. One way to solve this problem is to use Convolutional Neural Networks (CNN) have been applied in the field of medical imaging research and have successfully demonstrated their ability for image classification and recognition. Classifying the medical images by selecting the optimal features improves the performance of the classification process. Choosing the best features reduces the time and algorithm effort of the overall process. The main objective of the process is to select the optimal features from the different types of features extracted using different methods. Features were extracted from the images based on LBP features and CVH features. To use the best fit function based on Fisher's criterion to select the optimal features. Combining the fitness function with genetic optimization to improve the efficiency of the genetic algorithm. Feature extraction, optimization and classification play the efficient role to improve accuracy. The overall performance of was measured using performance metrics such as accuracy, sensitivity and specificity. |
| Keywords: | CT , LBP, CVH, CNN, Genetic algorithm |
| Cite Article: | "A semi automatic classification of Lung disease using CNN", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 3, page no.a290-a293, March-2023, Available :http://www.ijnrd.org/papers/IJNRD2303028.pdf |
| Downloads: | 000118746 |
| 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 |
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Published Paper ID:IJNRD2303028 Registration ID: 188168 Published In: Volume 8 Issue 3, March-2023 DOI (Digital Object Identifier): Page No: a290-a293 Country: kovilpatti, tamilnadu, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2303028 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2303028 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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