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Brain tumors represent a significant health concern globally, contributing to a high mortality rate. Timely detection and intervention are critical for improving patient outcomes. The proposed work focuses on brain tumor detection and classification using deep learning models. The system comprises key stages of data collection, preprocessing, feature extraction, and classification. Several deep learning models were evaluated for their performance. The results show that the DenseNet-121 model outperformed others with an accuracy of 97.69%. This proposed system offers a reliable and efficient approach to predicting brain tumor likelihood, serving as a valuable screening tool for early detection. This innovative system holds great promise as a reliable screening tool for early detection, poised to significantly enhance survival rates and mitigate the mortality associated with brain tumors. By offering medical practitioners an efficient tool for early disease detection, this intelligent model becomes a vital asset in the continuous efforts to address the impact of brain tumors on global health.

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Brain Tumor Detection and Classification Using Deep Learning Models

  • 会议论文

  • 发表日期：

    2025年

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  • Manjunath Pujar,
  • H. Kavanashree,
  • M. Jitendra,
  • Shankaraling Halemani,
  • Vidya Handur

摘要

Brain tumors represent a significant health concern globally, contributing to a high mortality rate. Timely detection and intervention are critical for improving patient outcomes. The proposed work focuses on brain tumor detection and classification using deep learning models. The system comprises key stages of data collection, preprocessing, feature extraction, and classification. Several deep learning models were evaluated for their performance. The results show that the DenseNet-121 model outperformed others with an accuracy of 97.69%. This proposed system offers a reliable and efficient approach to predicting brain tumor likelihood, serving as a valuable screening tool for early detection. This innovative system holds great promise as a reliable screening tool for early detection, poised to significantly enhance survival rates and mitigate the mortality associated with brain tumors. By offering medical practitioners an efficient tool for early disease detection, this intelligent model becomes a vital asset in the continuous efforts to address the impact of brain tumors on global health.