Intelligent Systems for Medical Imaging: Innovations and Applications of AI in Healthcare

This study explores the impact of artificial intelligence (AI) on medical imaging, emphasizing the improvements in operational efficiency and diagnostic accuracy. Deep learning and computer vision have been extensively studied for their ability to improve the analysis of medical images. Based on the findings, it is evident that AI-driven diagnostic tools exhibit a higher level of precision. These tools boast an impressive 90% accuracy rate when it comes to detecting conditions like breast cancer and lung nodules. Additionally, they have successfully reduced the time needed for picture analysis by 50%. Artificial intelligence (AI) often achieves high dice coefficients of over 0.85. It also improves patient outcomes by enabling early illness diagnosis and picture segmentation. The results presented in this study demonstrate the immense potential of artificial intelligence in transforming the field of medical imaging diagnosis, thereby enhancing the quality of patient care.

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Publication Details

Published
2024-09-20
DOI
https://doi.org/10.1109/icdscnc62492.2024.10939759
Primary Topic
Brain Tumor Detection and Classification
Type
article
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article

Intelligent Systems for Medical Imaging: Innovations and Applications of AI in Healthcare

Fazal Noorbasha, Seppo Kalli, Shastri Vishwashree
Brain Tumor Detection and Classification
article

Intelligent Systems for Medical Imaging: Innovations and Applications of AI in Healthcare

Fazal Noorbasha, Seppo Kalli, Shastri Vishwashree
article en

Abstract

This study explores the impact of artificial intelligence (AI) on medical imaging, emphasizing the improvements in operational efficiency and diagnostic accuracy. Deep learning and computer vision have been extensively studied for their ability to improve the analysis of medical images. Based on the findings, it is evident that AI-driven diagnostic tools exhibit a higher level of precision. These tools boast an impressive 90% accuracy rate when it comes to detecting conditions like breast cancer and lung nodules. Additionally, they have successfully reduced the time needed for picture analysis by 50%. Artificial intelligence (AI) often achieves high dice coefficients of over 0.85. It also improves patient outcomes by enabling early illness diagnosis and picture segmentation. The results presented in this study demonstrate the immense potential of artificial intelligence in transforming the field of medical imaging diagnosis, thereby enhancing the quality of patient care.

University College for Women (IN), Koneru Lakshmaiah Education Foundation (IN)
Industry, innovation and infrastructure
Openalex Percentile: Top 68%
Brain Tumor Detection and Classification
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