Segmentation Synergy with a Dual U-Net and Federated Learning with CNNRF Models for Enhanced Brain Tumor Analysis

The combined structure of the federated learning framework, CNN-RF hybrid model, and dual U-Net segmentation is a robust and privacypreserving approach for identifying MRI images from brain tumors. The results of the present study exhibited that the technique is promising in improving the quality of brain tumor categorization and provides a pathway for practical utilization in clinical settings.

Authors

Institutions

Publication Details

Journal
Current Medical Imaging Formerly Current Medical Imaging Reviews
Published
2024-09-19
DOI
https://doi.org/10.2174/0115734056312765240905104112
Citations
8
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
1.98
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Segmentation Synergy with a Dual U-Net and Federated Learning with CNNRF Models for Enhanced Brain Tumor Analysis

Bhawna Goyal, Vinay Kukreja, Shiva Mehta, Ayush Dogra et al.
8 citations
Current Medical Imaging Formerly Current Medical Imaging Reviews
Brain Tumor Detection and Classification
1.98
article

Segmentation Synergy with a Dual U-Net and Federated Learning with CNNRF Models for Enhanced Brain Tumor Analysis

Bhawna Goyal, Vinay Kukreja, Shiva Mehta, Ayush Dogra, Satvik Vats, Rajesh Kumar Kaushal
article en
8 citations

Abstract

The combined structure of the federated learning framework, CNN-RF hybrid model, and dual U-Net segmentation is a robust and privacypreserving approach for identifying MRI images from brain tumors. The results of the present study exhibited that the technique is promising in improving the quality of brain tumor categorization and provides a pathway for practical utilization in clinical settings.

Current Medical Imaging Formerly Current Medical Imaging ReviewsVol. 20
Chandigarh University (IN), Sohar University (OM), Graphic Era University (IN), Chitkara University (IN)
Openalex Percentile: Top 13%
Brain Tumor Detection and Classification
1.98
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Segmentation Synergy with a Dual U-Net and Federated Learning with CNNRF Models for Enhanced Brain Tumor Analysis — Bhawna Goyal, Vinay Kukreja, et al. · Current Medical Imaging Formerly Current Medical Imaging Reviews (2024) | TGRS Research Map | TGRS