International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 2 March-April 2024 Submit your research before last 3 days of April to publish your research paper in the issue of March-April.

Deep Learning Model with VGG16 Model for Brain Tumour Detection

Author(s) Mandeep Mehan, Dr. Harpreet Kaur, Dr. Neelofar Sohi
Country India
Abstract A mass or collection of abnormal brain cells is referred to as a brain tumour. The skull, in which the brain is housed, is exceedingly sturdy. There are several phases involved in the detection of brain tumours from biomedical images, including pre-processing, segmentation, feature extraction, and classification. The various schemes for the brain tumor detection are proposed in previous years but those schemes give low accuracy. In this paper, novel scheme is proposed which is based on transfer learning model. In the proposed scheme Parallel Non-Local Mean is used for the filtering and snake segmentation is used for the image segmentation. Transfer learning will be employed for classification in the final stage. The VGG16 and CNN models are combined to create the transfer learning model. Python will be used to implement the suggested model, and accuracy, precision, and recall will be evaluated of the outcomes.
Keywords Brain Tumour, Snake Segmentation, Parallel Non-Local Mean Filter, VGG16, CNN
Field Engineering
Published In Volume 6, Issue 1, January-February 2024
Published On 2024-01-04
Cite This Deep Learning Model with VGG16 Model for Brain Tumour Detection - Mandeep Mehan, Dr. Harpreet Kaur, Dr. Neelofar Sohi - IJFMR Volume 6, Issue 1, January-February 2024. DOI 10.36948/ijfmr.2024.v06i01.11612
DOI https://doi.org/10.36948/ijfmr.2024.v06i01.11612
Short DOI https://doi.org/gtdsch

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