SBTD: Secured Brain Tumor Detection in IoMT Enabled Smart Healthcare

Brain tumors are fatal and severely disrupt brain function as they advance. Timely detection and precise monitoring are crucial for improving patient outcomes and survival. A smart healthcare system leveraging the Internet of Medical Things (IoMT) revolutionizes patient care by offering streamlined remote healthcare, especially for individuals with acute medical conditions like brain tumors. However, such systems face significant challenges, such as 1) the increasing prevalence of cyber attacks in the expanding digital healthcare landscape, and 2) the lack of reliability and accuracy in existing tumor detection methods. To address these issues, we propose Secured Brain Tumor Detection (SBTD), the first unified system integrating IoMT with secure tumor detection. SBTD features: 1) a robust security framework grounded in chaos theory, to safeguard medical data; and 2) a reliable machine learning-based tumor detection framework that accurately localizes tumors using their anatomy. Comprehensive experimental evaluations on different multimodal MRI datasets demonstrate the system's suitability, clinical applicability and superior performance over state-of-the-art algorithms.

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Publication Details

Journal
IEEE Journal of Biomedical and Health Informatics
Published
2024-10-16
DOI
https://doi.org/10.1109/jbhi.2024.3482465
Citations
4
Primary Topic
Brain Tumor Detection and Classification
Type
article
Field-Weighted Citation Impact
0.99
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article

SBTD: Secured Brain Tumor Detection in IoMT Enabled Smart Healthcare

Gaurav Bhatnagar, Parkala Vishnu Bharadwaj Bayari, Nishtha Tomar
4 citations
IEEE Journal of Biomedical and Health Informatics
Brain Tumor Detection and Classification
0.99
article

SBTD: Secured Brain Tumor Detection in IoMT Enabled Smart Healthcare

Gaurav Bhatnagar, Parkala Vishnu Bharadwaj Bayari, Nishtha Tomar
article en
4 citations

Abstract

Brain tumors are fatal and severely disrupt brain function as they advance. Timely detection and precise monitoring are crucial for improving patient outcomes and survival. A smart healthcare system leveraging the Internet of Medical Things (IoMT) revolutionizes patient care by offering streamlined remote healthcare, especially for individuals with acute medical conditions like brain tumors. However, such systems face significant challenges, such as 1) the increasing prevalence of cyber attacks in the expanding digital healthcare landscape, and 2) the lack of reliability and accuracy in existing tumor detection methods. To address these issues, we propose Secured Brain Tumor Detection (SBTD), the first unified system integrating IoMT with secure tumor detection. SBTD features: 1) a robust security framework grounded in chaos theory, to safeguard medical data; and 2) a reliable machine learning-based tumor detection framework that accurately localizes tumors using their anatomy. Comprehensive experimental evaluations on different multimodal MRI datasets demonstrate the system's suitability, clinical applicability and superior performance over state-of-the-art algorithms.

IEEE Journal of Biomedical and Health InformaticsVol. 30(1)
Indian Institute of Technology Jodhpur (IN)
Industry, innovation and infrastructure
Openalex Percentile: Top 23%
Brain Tumor Detection and Classification
0.99
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SBTD: Secured Brain Tumor Detection in IoMT Enabled Smart Healthcare — Gaurav Bhatnagar, Parkala Vishnu Bharadwaj Bayari, et al. · IEEE Journal of Biomedical and Health Informatics (2024) | TGRS Research Map | TGRS