Effect of optode geometry and regularization methods on low‑cost diffuse optical tomography systems

Uysal H., Uysal S., Kazancı H. Ö., Sedef H.

OPTICAL AND QUANTUM ELECTRONICS, cilt.55, sa.60, ss.1-24, 2022 (SCI-Expanded)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 55 Sayı: 60
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1007/s11082-022-04366-4
  • Dergi Adı: OPTICAL AND QUANTUM ELECTRONICS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.1-24
  • Akdeniz Üniversitesi Adresli: Evet

Özet

The forward and inverse problem are the important parts of the Difuse Optical Tomography system. As well as the correct determination of the optode number and good placement of the source-detector matches, the regularization method to be used relative to the selected geometry is also important. The higher the number of source-detector, the higher cost and computation time. These parameters can be reduced with a correct placement. The aim of this study is to show that the success to be obtained from a vast amount of source detector matches can also be obtained from few number of source detector matches with the correct regularization method and optode geometry. In this paper, a low cost and efective optode geometry was studied. Firstly a custom optode geometry was designed. In addition to this geometry, four diferent source-detector placements that are frequently used in other studies were selected to test the performance of proposed optode geometry. Then forward model weight matrix was generated for all geometries. Ordinary Least Squares, Least Absolute Shrinkage and Selection Operator Regression, Ridge Regression and Elastic-Net regularization methods were used to solve inverse problem. The quality of the reconstructed images of optode geometries were examined by comparing synthetic data with and without noise. The results show that the proposed geometry and the correct regularization method has better estimation accuracy and lower computation time more robust to noise than the other cost-efective geometries.