International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Transfer Learning To Predict Tumor Type and Grade by Magnetic Resonance Spectroscopy

Abstract

Glioblastoma Multiforme is a high grade, very aggressive brain tumor. But Gliomas is a low grade, which is less aggressive, but they can evolve into higher grade tumors over time. Tumor grading is important for sufficient treatment planning and monitoring. As we know the "perfect" method to grade a tumor is by the histopathological diagnosis of biopsy specimens. But, this procedure is invasive, time consuming, and prone to sampling error (rare) but for many cases surgery is not possible. Because of these disadvantages, automatic tumor grading from widely used MRI protocols would be clinically important, for the treatment planning and assessment of tumor. In this project, we propose to use transfer learning to predict tumor type and grade by Magnetic Resonance Spectroscopy. In this way, we will overcome the need for expert annotations for marking the important regions of interest and tumor those images that required a radiologist to classify and analyse will only require the nurse. 

Country : India

1 Boini Nareshkumar

  1. Associate Professor, Department of Electronics and Communication Engineering, Malla Reddy College of Engineering for Women, Hyderabad -500100, Telangana, India

IRJIET, Volume 2, Issue 1, March 2018 pp. 61-66

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