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IJIEE
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DOI: 10.62674/ijiee.2025.v2i01.001
Published: 2025-03-24

Advancing Brain Tumor Diagnosis Using Deep Learning and Automated Imaging Techniques

Department of ECE, KLM College of Engineering for Women, Kadapa, A.P – India
Dr. YSR Architecture and Fine Arts University, Kadapa, A.P – India – 516003
Department of H&S, KLM College of Engineering for Women, Kadapa
Department of AI&ML, KLM College of Engineering for Women, Kadapa, A.P – India
Department of ECE, Annamacharya Institute of Technology & Sciences, Kadapa – AP
Department of ECE, Sasi Institute of Technology & Engineering, Tadepalligudem, AP
Brain Tumor Deep Learning Automated Image Techniques CNN Magnetic Resonance Imaging

Abstract

The study of tumor detection in brain is aimed for improvement of the required treatment for people that are suffering from brain tumor (BT). Brain tumors are aberrant cell evolutions in the brain, while cancer is an acronym employing to indicate tumors that are cancerous called malignant. CT or MRI investigations are used often to identify malignant regions in the brain. PET, cerebral arteriogram (CA), lumbar puncture (LP), and molecular testing (MT) can also be used to detect BTs. MRI scans are largely used in this investigation to examine the illness condition. The objectives of this study are to detect aberrant images and segment the tumor territory. The segmented mask can measure tumor density for therapeutic purposes.

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How to Cite

T. Lakshmi Narayana, P. Uma Devi, G. Rajeswari, B. Mahesh Nayak, P. Anjaneya, & T. Venkatakrishnamoorthy. (2025). Advancing Brain Tumor Diagnosis Using Deep Learning and Automated Imaging Techniques. International Journal of Interpreting Enigma Engineers (IJIEE), 2(1), 1–9. https://doi.org/10.62674/ijiee.2025.v2i01.001

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