Retinal OCT Segmentation Using Fuzzy Region Competition and Level Set Methods
| Autor: | Bashir Isa Dodo, Allan Tucker, Yongmin Li, Xiaohui Liu, Djibril Kaba |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Level set method
genetic structures medicine.diagnostic_test business.industry Computer science 0206 medical engineering Pattern recognition 02 engineering and technology Image segmentation 020601 biomedical engineering 01 natural sciences Fuzzy logic 010309 optics Level set Optical coherence tomography Region of interest 0103 physical sciences medicine Segmentation sense organs Artificial intelligence Cluster analysis business |
| Zdroj: | CBMS |
| DOI: | 10.1109/cbms.2019.00029 |
| Popis: | Optical coherence tomography (OCT) is a noninvasive imaging modality that provides in-depth images of the retina. Properties of individual layers on OCT have become important markers for diagnosing and tracking medication of various eye diseases in current ophthalmology. Manual segmentation of OCT scans posed many challenges (errors, inconsistency), which can be addressed by automated segmentation methods. Level set method is one of the most popular methods in the literature used for this purpose. Although level set methods have a fundamental way of handling topological changes, the weak boundaries and noise in addition to inhomogeneity in OCT images make it difficult to segment the layers accurately. Inspired by the concept of region competition, we incorporate prior knowledge of the retinal structure to segment nine (9) layers of the retina. Mainly, we establish a specific region of interest, then use selected components from fuzzy C-Means for initialisation. The clustering in the initialisation stage is also used to guide the evolution through; a Mumford-Shah (MS) selective region competition force and a Hamilton-Jacobi (HJ) balloon force. The forces ensure evolution close to actual retinal boundaries. Finally, the convergence of the method is based on an improved HJ object indication function influenced by the fuzzy membership to prevent leakages at weak boundaries. Experimental results are promising based on 200 OCT images. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|