论文信息 - Extracting diagnostic information from optical coherence tomography images of diabetic retinal tissues using depthdependent attenuation rate and fractal analysis.

Extracting diagnostic information from optical coherence tomography images of diabetic retinal tissues using depthdependent attenuation rate and fractal analysis.

The sensitivity of OCT images to sample diabetic morphology is tested by calculating attenuation coefficients and fractal dimension. Fractal analysis provided a better sensitivity, offering a potential diagnostic predictor for detecting early diabetic retinopathy.

[1] Carmen A Puliafito,et al. Automated detection of retinal layer structures on optical coherence tomography images. , 2005, Optics express.

[2] Gabriele A. Losa,et al. Ultrastructural Complexity of Nuclear Components During Early Apoptotic Phases in Breast Cancer Cells , 2001, Analytical cellular pathology : the journal of the European Society for Analytical Cellular Pathology.

[3] Carmen A. Puliafito,et al. Automatic retinal blood flow calculation using spectral domain optical coherence tomography , 2007 .

[4] Dirk Faber,et al. Functional optical coherence tomography : spatially resolved measurements of optical properties , 2005 .

[5] Chunxin Yang,et al. Evaluation of the wavelet transform method for machined surface topography I: methodology validation , 2003 .