Modified watershed approach for segmentation of complex optical coherence tomographic images

TL;DR

This paper introduces a modified watershed segmentation algorithm tailored for complex optical coherence tomography images, effectively addressing over-segmentation issues caused by noise in medical imaging applications.

Contribution

A novel modified watershed algorithm is proposed, improving segmentation accuracy of OCT images by reducing over-segmentation in noisy environments.

Findings

Effective segmentation of lemon internal structures

Reduced over-segmentation in noisy OCT images

Promising results for medical imaging applications

Abstract

Watershed segmentation method has been used in various applications. But many a times, due to its over-segmentation attributes, it underperforms in several tasks where noise is a dominant source. In this study, Optical Coherence Tomography images have been acquired, and segmentation has been performed to analyse the different regions of fluid filled sacs in a lemon. A modified watershed algorithm has been proposed which gives promising results for segmentation of internal lemon structures.