A benchmark study of automated intra-retinal cyst segmentation algorithms using optical coherence tomography B-scans

(BACKGROUND AND OBJECTIVES) Retinal cysts are formed by accumulation of fluid in the retina caused by leakages from inflammation or vitreous fractures. Analysis of the retinal cystic spaces holds significance in detection and treatment of several ocular diseases like age-related macular degeneration, diabetic macular edema etc. Thus, segmentation of intra-retinal cysts and quantification of cystic spaces are vital for retinal pathology and severity detection. In the recent years, automated segmentation of intra-retinal cysts using optical coherence tomography B-scans has gained significant importance in the field of retinal image analysis. The objective of this paper is to compare different intra-retinal cyst segmentation algorithms for comparative analysis and benchmarking purposes. (METHODS) In this work, we employ a modular approach for standardizing the different segmentation algorithms. Further, we analyze the variations in automated cyst segmentation performances and method scalability across image acquisition systems by using the publicly available cyst segmentation challenge dataset (OPTIMA cyst segmentation challenge). (RESULTS) Several key automated methods are comparatively analyzed using quantitative and qualitative experiments. Our analysis demonstrates the significance of variations in signal-to-noise ratio (SNR), retinal layer morphology and post-processing steps on the automated cyst segmentation processes. (CONCLUSION) This benchmarking study provides insights towards the scalability of automated processes across vendor-specific imaging modalities to provide guidance for retinal pathology diagnostics and treatment processes.

[1]  Marilita M Moschos,et al.  Cystoid macular edema , 2008, Clinical Ophthalmology.

[2]  Roberto Manduchi,et al.  Bilateral filtering for gray and color images , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[3]  S. R. Irvine.  A newly defined vitreous syndrome following cataract surgery. , 1953, American journal of ophthalmology.

[4]  J. Hornegger,et al.  Retinal Nerve Fiber Layer Segmentation on FD-OCT Scans of Normal Subjects and Glaucoma Patients , 2010, Biomedical optics express.

[5]  Wojciech Wieclawek.  Automatic cysts detection in optical coherence tomography images , 2015, 2015 22nd International Conference Mixed Design of Integrated Circuits & Systems (MIXDES).

[6]  Jeny Rajan,et al.  Automated segmentation of intra-retinal cysts from optical coherence tomography scans using marker controlled watershed transform , 2016, EMBC.

[7]  Delia Cabrera Fernandez,et al.  Delineating fluid-filled region boundaries in optical coherence tomography images of the retina , 2005, IEEE Transactions on Medical Imaging.

[8]  M. Sonka,et al.  Retinal Imaging and Image Analysis , 2010, IEEE Reviews in Biomedical Engineering.

[9]  Yalin Zheng,et al.  Computerized assessment of intraretinal and subretinal fluid regions in spectral-domain optical coherence tomography images of the retina. , 2013, American journal of ophthalmology.

[10]  Keshab K. Parhi,et al.  Automated localization of cysts in diabetic macular edema using optical coherence tomography images , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[11]  L. R. Dice.  Measures of the Amount of Ecologic Association Between Species , 1945 .

[12]  Xinjian Chen,et al.  Three-Dimensional Segmentation of Fluid-Associated Abnormalities in Retinal OCT: Probability Constrained Graph-Search-Graph-Cut , 2012, IEEE Transactions on Medical Imaging.

[13]  Georg Langs,et al.  Automatic segmentation and classification of intraretinal cystoid fluid and subretinal fluid in 3D-OCT using convolutional neural networks , 2015 .

[14]  Jeny Rajan,et al.  Marker controlled watershed transform for intra-retinal cysts segmentation from optical coherence tomography B-scans , 2017, Pattern Recognit. Lett..

[15]  Xinjian Chen,et al.  Automated segmentation of intraretinal cystoid macular edema for retinal 3D OCT images with macular hole , 2015, 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI).

[16]  Amy L. Oldenburg,et al.  Automated Segmentation of Intraretinal Cystoid Fluid in Optical Coherence Tomography , 2012, IEEE Transactions on Biomedical Engineering.

[17]  Matthäus Pilch,et al.  Automated segmentation of pathological cavities in optical coherence tomography scans. , 2013, Investigative ophthalmology & visual science.

[18]  Sobha Sivaprasad,et al.  Prevalence of diabetic retinopathy in various ethnic groups: a worldwide perspective. , 2012, Survey of ophthalmology.

[19]  Jeny Rajan,et al.  TEMPORARY REMOVAL: Marker controlled watershed transform for intra-retinal cysts segmentation from optical coherence tomography B-scans , 2017 .

[20]  Sina Farsiu,et al.  Kernel regression based segmentation of optical coherence tomography images with diabetic macular edema. , 2015, Biomedical optics express.

[21]  Peter A. Calabresi,et al.  Segmentation of microcystic macular edema in Cirrus OCT scans with an exploratory longitudinal study , 2015, Medical Imaging.

[22]  Jeny Rajan,et al.  Enhancement and bias removal of optical coherence tomography images: An iterative approach with adaptive bilateral filtering , 2016, Comput. Biol. Medicine.

[23]  Jerry L Prince,et al.  Automatic segmentation of microcystic macular edema in OCT. , 2014, Biomedical optics express.

[24]  Milan Sonka,et al.  Three-Dimensional Analysis of Retinal Layer Texture: Identification of Fluid-Filled Regions in SD-OCT of the Macula , 2010, IEEE Transactions on Medical Imaging.

[25]  Beatriz Remeseiro,et al.  Automatic cyst detection in OCT retinal images combining region flooding and texture analysis , 2013, Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems.

[26]  Peter A. Calabresi,et al.  Microcystic macular edema detection in retina OCT images , 2014, Medical Imaging.

[27]  Xiaodong Wu,et al.  Automated 3-D Intraretinal Layer Segmentation of Macular Spectral-Domain Optical Coherence Tomography Images , 2009, IEEE Transactions on Medical Imaging.

[28]  J. Fujimoto,et al.  Optical Coherence Tomography , 1991 .

[29]  Xiaodong Wu,et al.  Optimal Surface Segmentation in Volumetric Images-A Graph-Theoretic Approach , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.