Barton, J., Gossage, K. W., Tkaczyk, T. S., Rodriguez, J. J., & Barton, J. K. (2003). Texture analysis of optical coherence tomography images: feasibility for tissue classification. Journal of biomedical optics, 8(3).
Optical coherence tomography (OCT) acquires cross-sectional images of tissue by measuring back-reflected light. Images from in vivo OCT systems typically have a resolution of 10 to 15 mm, and are thus best suited for visualizing structures in the range of tens to hundreds of microns, such as tissue layers or glands. Many normal and abnormal tissues lack visible structures in this size range, so it may appear that OCT is unsuitable for identification of these tissues. However, examination of structure-poor OCT images reveals that they frequently display a characteristic texture that is due to speckle. We evaluated the application of statistical and spectral texture analysis techniques for differentiating tissue types based on the structural and speckle content in OCT images. Excellent correct classification rates were obtained when images had slight visual differences (mouse skin and fat, correct classification rates of 98.5 and 97.3%, respectively), and reasonable rates were obtained with nearly identical-appearing images (normal versus abnormal mouse lung, correct classification rates of 64.0 and 88.6%, respectively). This study shows that texture analysis of OCT images may be capable of differentiating tissue types without reliance on visible structures.
Wall, R. A., Bonnema, G. T., & Barton, J. K. (2011). Novel focused OCT-LIF endoscope. BIOMEDICAL OPTICS EXPRESS, 2(3), 421-430.
Watson, J. M., Rice, P. F., Marion, S. L., Brewer, M. A., Davis, J. R., Rodriguez, J. J., Utzinger, U., Hoyer, P. B., & Barton, J. K. (2012). Analysis of Second-Harmonic Generation Microscopy in a Mouse Model of Ovarian Carcinoma. Journal of Biomedical Optics, 17(7), 076002-1 to 076002-9.
Barton, J. K., Barton, J. K., Rice, P. F., Marion, S. L., Brewer, M. A., Davis, J. R., Rodriguez, J. J., Utzinger, U., Hoyer, P. B., & Barton, J. K. (2012). Analysis of second-harmonic-generation microscopy in a mouse model of ovarian carcinoma. Journal of biomedical optics, 17(7).
Second-harmonic-generation (SHG) imaging of mouse ovaries ex vivo was used to detect collagen structure changes accompanying ovarian cancer development. Dosing with 4-vinylcyclohexene diepoxide and 7,12-dimethylbenz[a]anthracene resulted in histologically confirmed cases of normal, benign abnormality, dysplasia, and carcinoma. Parameters for each SHG image were calculated using the Fourier transform matrix and gray-level co-occurrence matrix (GLCM). Cancer versus normal and cancer versus all other diagnoses showed the greatest separation using the parameters derived from power in the highest-frequency region and GLCM energy. Mixed effects models showed that these parameters were significantly different between cancer and normal (P0.008). Images were classified with a support vector machine, using 25% of the data for training and 75% for testing. Utilizing all images with signal greater than the noise level, cancer versus not-cancer specimens were classified with 81.2% sensitivity and 80.0% specificity, and cancer versus normal specimens were classified with 77.8% sensitivity and 79.3% specificity. Utilizing only images with greater than of 75% of the field of view containing signal improved sensitivity and specificity for cancer versus normal to 81.5% and 81.1%. These results suggest that using SHG to visualize collagen structure in ovaries could help with early cancer detection.
Black, J., Tate, T., Keenan, M., Swan, E., Utzinger, U., & Barton, J. (2015). A Six-Color Four-Laser Mobile Platform for Multi-Spectral Fluorescence Imaging Endoscopy. 2015 CONFERENCE ON LASERS AND ELECTRO-OPTICS (CLEO).
