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Can we see epithelium tissue structure below the surface using an optical probe?

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Abstract

This paper answers the question of whether it is possible to detect changes below the surface in epithelium layered structures using a Stochastic Decomposition Method (SDM) that models the scattered light reflected from the layered structure over an area (2-D scan) illuminated by an optical sensor (fibre) emitting light at either one wavelength or with white light. Our technique correlates the differential changes in the reflected tissue texture with the morphological and physical changes that occur in the tissue occurring inside the structure. This work has great potential for detecting changes in mucosal structures and may lead to enhanced endoscopy when the disease is developing to the outside of the mucosal structure and hence becoming hidden during colonoscopy or endoscopic examination. Tests are performed on layered tissue phantoms, and the results obtained show great effectiveness of the model and method in picking up changes in the morphology of the layered tissue phantoms occurring below the surface. We also establish the robustness of the model to changes in viewing depth by testing it on phantoms viewed at different depths. We show that the model is robust to within a 4-mm-deep viewing range.

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Acknowledgments

We would like to thank Photonics Lab members: Ms. Elina Vitol, Dr. Timothy Kurzweg and Dr. Bahram Nabet in the ECE Dept. at Drexel University for providing the optical device (probe, spectrometer and light source) and the phantoms used in this research. Special thanks are also due Ms. Elina Vitol for preparing the multi-layered tissue phantoms. We also thank Dr. Jim Reynolds from Drexel College of Medicine for many useful discussions on the subject of light endoscopy.

Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Drexel University, Philadelphia, PA, USA

    Fernand S. Cohen & Ezgi Taslidere

  2. Division of Gastroenterology and Hepatology, College of Medicine, Drexel University, Philadelphia, PA, USA

    Sreekant Murthy

Authors
  1. Fernand S. Cohen
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  2. Ezgi Taslidere
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  3. Sreekant Murthy
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Corresponding author

Correspondence to Ezgi Taslidere.

Additional information

Part of this work has been published in the peer-reviewed IEEE International Symposium on Biomedical Imaging (ISBI 2008): From Nano to Macro; Paris, France, 14–17 May 2008 [1]. F. S. Cohen, E. Taslidere, and S. Murthy, “Classification of layered tissue phantoms for detection of changes in epithelial tissue below the surface using a stochastic decomposition model for scattered signal,” in 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro. ISBI 2008, Paris, France, May 14–17, 2008, pp. 1211–1214.

Fernand S. Cohen and Ezgi Taslidere contributed equally to this work.

Appendix

Appendix

In this section, we take the reader through every step of our technique by showing the details on a real worked-out example that shows the raw 1D scan data for each structure, the fitted parameters of AR process and the d metric obtained based on a specific parameter of the AR process when comparing two 1D scans. It also shows the evaluated threshold 2σd that the metric dγ,λ is compared to in order to arrive at the binary decision (the two scans belong to the same or to different structures) for the selected example. The details of the data collection process using the experimental setup shown in Fig. 5 are given in Fig. 7, and it results into the 1D scans of the samples shown at the top left-hand side of Fig. 8. Then AR process is fitted on those signals, and the AR parameters are extracted. The goodness of the AR model is shown in Fig. 8a, top right hand side; which shows typical realizations of the fitted AR process. As we can see, the AR process captures well the 1D raw data scan characteristics for both structures. Based on the fitted AR parameters, σd is computed for each nominal model as explained in Sect. 2.2.2. For the two samples shown in Fig. 7a, the dγ,λ metric between two samples for each individual parameter (shown in Fig. 8b) for just the parameter) is calculated and expressed as function of the corresponding σd for the nominal model. For this data set, the dγ,λ is found to be 31σd, which is well above the threshold 2σd, resulting in the decision that the two scans originated from two different structures.

Fig. 7
figure 7

Zooming into the data collection process using the setup shown in Fig. 5

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Fig. 8
figure 8

Steps of the technique are shown for a sample data pair in detail; from the raw the 1D scan data for each structure, to the fitted parameters of AR process and to the d metric obtained based on a specific parameter of the AR process when comparing two 1D scans. The details are shown for a typical realizations of the AR process for sample 1D scans, b decision-making process for the parameter

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Cohen, F.S., Taslidere, E. & Murthy, S. Can we see epithelium tissue structure below the surface using an optical probe?. Med Biol Eng Comput 49, 85–96 (2011). https://doi.org/10.1007/s11517-010-0672-4

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