Deep Learning Based Method for Brain Tumor Detection

A brain tumour is considered to be a group of anomalous cells in the brain. The skull is very hard where the brain is enclosed. The growth of any type of tumour in this restricted area causes many problems. The brain tumour is detected in various steps such as to pre-process the image, segment it, extract the features and classify the tumor. In the previous research work, numerous techniques are proposed which include snake segmentation for the segmentation, image filtering using PNLM filtering techniques. In the last transfer learning will be used for the classification. The transfer learning model is the combination of VGG16 and CNN models. Python is executed to simulate the introduced model. Accuracy, precision and recall are employed for computing the results. The proposed model shows high accuracy in comparison with existing ML models for the brain tumour detection

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-06-06
DOI
https://doi.org/10.52783/jisem.v10i54s.11057
Primary Topic
Brain Tumor Detection and Classification
Type
article
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article

Deep Learning Based Method for Brain Tumor Detection

Mandeep Kaur
Journal of Information Systems Engineering & Management
Brain Tumor Detection and Classification
article

Deep Learning Based Method for Brain Tumor Detection

Mandeep Kaur
article en

Abstract

A brain tumour is considered to be a group of anomalous cells in the brain. The skull is very hard where the brain is enclosed. The growth of any type of tumour in this restricted area causes many problems. The brain tumour is detected in various steps such as to pre-process the image, segment it, extract the features and classify the tumor. In the previous research work, numerous techniques are proposed which include snake segmentation for the segmentation, image filtering using PNLM filtering techniques. In the last transfer learning will be used for the classification. The transfer learning model is the combination of VGG16 and CNN models. Python is executed to simulate the introduced model. Accuracy, precision and recall are employed for computing the results. The proposed model shows high accuracy in comparison with existing ML models for the brain tumour detection

Journal of Information Systems Engineering & ManagementVol. 10(54s)
Openalex Percentile: Top 83%
Brain Tumor Detection and Classification
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