Mr. Michalis Kassinopoulos Profile

Michalis Kassinopoulos

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Proceedings Article | 14 February 2018 Paper

Automated detection of esophageal dysplasia in in vivo optical coherence tomography images of the human esophagus

Michalis Kassinopoulos, Jing Dong, Guillermo Tearney, Costas Pitris

Proceedings Volume 10483, 104830R (2018) https://doi.org/10.1117/12.2289612

KEYWORDS: Optical coherence tomography, Esophagus, Tissues, In vivo imaging, Image segmentation, Data acquisition, Endoscopy, Biopsy, Intelligence systems, Imaging systems

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Catheter-based Optical Coherence Tomography (OCT) devices allow real-time and comprehensive imaging of the human esophagus. Hence, they provide the potential to overcome some of the limitations of endoscopy and biopsy, allowing earlier diagnosis and better prognosis for esophageal adenocarcinoma patients. However, the large number of images produced during every scan makes manual evaluation of the data exceedingly difficult. In this study, we propose a fully automated tissue characterization algorithm, capable of discriminating normal tissue from Barrett’s Esophagus (BE) and dysplasia through entire three-dimensional (3D) data sets, acquired in vivo. The method is based on both the estimation of the scatterer size of the esophageal epithelial cells, using the bandwidth of the correlation of the derivative (COD) method, as well as intensity-based characteristics. The COD method can effectively estimate the scatterer size of the esophageal epithelium cells in good agreement with the literature. As expected, both the mean scatterer size and its standard deviation increase with increasing severity of disease (i.e. from normal to BE to dysplasia). The differences in the distribution of scatterer size for each tissue type are statistically significant, with a p value of < 0.0001. However, the scatterer size by itself cannot be used to accurately classify the various tissues. With the addition of intensity-based statistics the correct classification rates for all three tissue types range from 83 to 100% depending on the lesion size.

Proceedings Article | 8 March 2016 Presentation + Paper

Development of a new, robust and accurate, spectroscopic metric for scatterer size estimation in optical coherence tomography (OCT) images

Michalis Kassinopoulos, Costas Pitris

Proceedings Volume 9697, 96971V (2016) https://doi.org/10.1117/12.2214112

KEYWORDS: Optical coherence tomography, Spectroscopy, Imaging spectroscopy, Mie scattering, Backscatter, Colon, Tissues, Biological research, Biopsy

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The modulations appearing on the backscattering spectrum originating from a scatterer are related to its diameter as described by Mie theory for spherical particles. Many metrics for Spectroscopic Optical Coherence Tomography (SOCT) take advantage of this observation in order to enhance the contrast of Optical Coherence Tomography (OCT) images. However, none of these metrics has achieved high accuracy when calculating the scatterer size. In this work, Mie theory was used to further investigate the relationship between the degree of modulation in the spectrum and the scatterer size. From this study, a new spectroscopic metric, the bandwidth of the Correlation of the Derivative (COD) was developed which is more robust and accurate, compared to previously reported techniques, in the estimation of scatterer size. The self-normalizing nature of the derivative and the robustness of the first minimum of the correlation as a measure of its width, offer significant advantages over other spectral analysis approaches especially for scatterer sizes above 3 μm. The feasibility of this technique was demonstrated using phantom samples containing 6, 10 and 16 μm diameter microspheres as well as images of normal and cancerous human colon. The results are very promising, suggesting that the proposed metric could be implemented in OCT spectral analysis for measuring nuclear size distribution in biological tissues. A technique providing such information would be of great clinical significance since it would allow the detection of nuclear enlargement at the earliest stages of precancerous development.

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