An Efficient Neuro-framework for Brain Tumor Classification Usinga CNN-based Self-supervised Learning Approach with GeneticOptimizations

The proposed framework offers an accurate and scalable solution for glioma classification from MRI images. It supports faster, more reliable clinical decision-making and holds promise for real-world diagnostic applications.

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Publication Details

Journal
Current Neuropharmacology
Published
2025-09-18
DOI
https://doi.org/10.2174/011570159x378103250806214613
Citations
7
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
5.90
Controls
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article

An Efficient Neuro-framework for Brain Tumor Classification Usinga CNN-based Self-supervised Learning Approach with GeneticOptimizations

Pappula Praveen, Pundru Chandra Shaker Reddy, Paripelli Ravali
7 citations
Current Neuropharmacology
Brain Tumor Detection and Classification
5.90
article

An Efficient Neuro-framework for Brain Tumor Classification Usinga CNN-based Self-supervised Learning Approach with GeneticOptimizations

Pappula Praveen, Pundru Chandra Shaker Reddy, Paripelli Ravali
article en
7 citations

Abstract

The proposed framework offers an accurate and scalable solution for glioma classification from MRI images. It supports faster, more reliable clinical decision-making and holds promise for real-world diagnostic applications.

Current NeuropharmacologyVol. 23
Amity University (IN), Amity University (AE)
Openalex Percentile: Top 4%
Brain Tumor Detection and Classification
5.90
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