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Original Article

Machine Learning-Driven Analysis of Liver Lesions from Medical Images

Open Access Peer Reviewed

Authors

  • Bharath N Y1
  • Bhimesha V J2
  • Chandresh M3
  • Pramod kumar H R4
  • Lakshmi D L5
  • Goutham V6

123456Department of Electronics and Communication Engineering, BGS Institute of Technology, Adichunchanagiri University, Mandya, Karnataka, India.

Article Information

DOI
No DOI
Published Online
May-June 2025
Pages
94-98
Article Type
Original Article
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No DOI available for cross-reference

Abstract

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Liver lesions are abnormal areas in the liver that may be harmless or a sign of serious diseases like cancer. Detecting and correctly identifying these lesions is important for early treatment. Traditionally, doctors analyze medical images like CT or MRI scans to find and classify these lesions. However, this process can be time-consuming and may vary between doctors. In this project, we use machine learning – a type of artificial intelligence – to help automatically analyze medical images and classify liver lesions. By training the system on a large number of labeled images, the computer learns to recognize patterns and make predictions about new, unseen images. This approach can support doctors by providing fast, consistent, and accurate results. Our study shows that machine learning can be a powerful tool in medical imaging and may help improve the early diagnosis and treatment of liver-related diseases.

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