Design of Microwave-based Brain Tumor Detection Framework with the Development of Sparse and Low-Rank Compressive Sensing Image Reconstruction

Hermawan Rahman Sholeh, Mia Rizkinia, Basari Basari

Research output: Contribution to journalArticlepeer-review

Abstract

Cancer is one of the leading causes of death, and the brain is one of the body's cancer-prone organs. The early detection of brain tumors can reduce cancer risk, which is practically assisted and conducted using scanners such as computed tomography (CT) and magnetic resonance imaging (MRI). However, those modalities are high-cost and large-sized, and they have a side effect risk to health. Alternatively, microwave imaging offers a novel cancer scanning method for early detection with low cost, small size and low health risk. Consequently, this research designs and creates a framework with a novel microwave image reconstruction algorithm inside. The framework is a component of the controller and image reconstructor for a portable microwave-based brain tumor detector that is open source and multi-platform. For the novel algorithm, this research proposes a CS-based imaging algorithm by exploiting the data's sparse and low-rank properties. The experiment shows that the proposed algorithm can give better qualitative and quantitative reconstruction results compared to a full-sampling-based as well as CS-based algorithm.

Original languageEnglish
Pages (from-to)984-994
Number of pages11
JournalInternational Journal of Technology
Volume11
Issue number5
DOIs
Publication statusPublished - 20 Nov 2020

Keywords

  • Compressive sensing
  • Framework
  • Image reconstruction
  • Low-rank
  • Microwave imaging
  • Sparse

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