A dynamic threshold segmentation algorithm for anterior chamber OCT images based on wavelet transform

In this paper, a dynamic threshold segmentation (DTS) algorithm based on wavelet transform is presented for anterior chamber Optical Coherence Tomography (OCT) images. This algorithm can reduce the speckle noise while preserve the edge of region of interest (ROI) which is anterior chamber in OCT images. Therefore it defines two thresholds, one of which is used to determine a ROI as the region of interest discrimination threshold (ROIDT), the other, defined as the noise threshold (NT), is to reduce noise from the region of interest which is gotten by the ROIDT. For better denoise effect, basic mathematical morphology and median filtering have been used to do further reduction on the segmented image and the Kirsch edge detection operator is selected to detect the edge of anterior chamber OCT image which has been denoised. To evaluate this proposed algorithm, the results are compared with two noise reduction methods, which are traditional Otsu algorithm and wavelet filtering. Experimental results show that the algorithm proposed can preserve more details while eliminating noise for edge detection of OCT images.