Multivariate Brain Tumor Detection in 3D‐MRI Images Using Optimised Segmentation and Unified Classification Model

The results obtained for the BraTS2020 and Brain Tumor Detection 2020 data sets showed that the proposed model outperforms existing techniques with excellent precision of 97%, 97.5%, recall of 99%, 97.8%, and accuracy of 95.7%, 98.4%, respectively.

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Publication Details

Journal
Journal of Evaluation in Clinical Practice
Published
2024-11-20
DOI
https://doi.org/10.1111/jep.14229
Citations
2
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.49
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article

Multivariate Brain Tumor Detection in 3D‐MRI Images Using Optimised Segmentation and Unified Classification Model

V. R. Anitha
2 citations
Journal of Evaluation in Clinical Practice
Brain Tumor Detection and Classification
0.49
article

Multivariate Brain Tumor Detection in 3D‐MRI Images Using Optimised Segmentation and Unified Classification Model

V. R. Anitha
article en
2 citations

Abstract

The results obtained for the BraTS2020 and Brain Tumor Detection 2020 data sets showed that the proposed model outperforms existing techniques with excellent precision of 97%, 97.5%, recall of 99%, 97.8%, and accuracy of 95.7%, 98.4%, respectively.

Journal of Evaluation in Clinical PracticeVol. 31(1)
SRM Institute of Science and Technology (IN)
Openalex Percentile: Top 33%
Brain Tumor Detection and Classification
0.49
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Multivariate Brain Tumor Detection in 3D‐MRI Images Using Optimised Segmentation and Unified Classification Model — V. R. Anitha · Journal of Evaluation in Clinical Practice (2024) | TGRS Research Map | TGRS