Automatic segmentation of foveal avascular zone based on adaptive watershed algorithm in retinal optical coherence tomography angiography images

Liu, Jian; Yan, Shixin; Lu, N.; Yang, Dongni; Fan, Chunhai; Lv, Hongyu; Wang, Shuanglian; Zhu, Xin; Zhao, Yuqian; Wang, Yi; Ma, Zhenhe; Yu, Yao

doi:10.1142/s1793545822420019

Cited by 11 publications

(5 citation statements)

References 24 publications

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“…In addition, a few studies assessing the accuracy of FAZ delineation in OCTA images of diabetic eyes have obtained poor results due to the high incidence of signal noise and artefacts in OCTA imaging of diabetic patients [ 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 ]. However, some authors such as Liu et al proposed the application of the watershed algorithm in FAZ segmentation for analysing and diagnosing eye diseases [ 40 ].…”

Section: Discussionmentioning

confidence: 99%

A Reliable Criterion for the Correct Delimitation of the Foveal Avascular Zone in Diabetic Patients

Fernández-Espinosa,

Ruiz-Tabuenca,

Orduna-Hospital

et al. 2023

JPM

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Background: Manual segmentation of the Foveal Avascular Zone (FAZ) has a high level of variability. Research into retinas needs coherent segmentation sets with low variability. Methods: Retinal optical coherence tomography angiography (OCTA) images from type-1 diabetes mellitus (DM1), type-2 diabetes mellitus (DM2) and healthy patients were included. Superficial (SCP) and deep (DCP) capillary plexus FAZs were manually segmented by different observers. After comparing the results, a new criterion was established to reduce variability in the segmentations. The FAZ area and acircularity were also studied. Results: The new segmentation criterion produces smaller areas (closer to the real FAZ) with lower variability than the different criteria of the explorers in both plexuses for the three groups. This was particularly noticeable for the DM2 group with damaged retinas. The acircularity values were also slightly reduced with the final criterion in all groups. The FAZ areas with lower values showed slightly higher acircularity values. We also have a consistent and coherent set of segmentations with which to continue our research. Conclusions: Manual segmentations of FAZ are generally carried out with little attention to the consistency of the measurements. A novel criterion for segmenting the FAZ allows segmentations made by different observers to be more similar.

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Section: Discussionmentioning

confidence: 99%

A Reliable Criterion for the Correct Delimitation of the Foveal Avascular Zone in Diabetic Patients

Fernández-Espinosa,

Ruiz-Tabuenca,

Orduna-Hospital

et al. 2023

JPM

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“…The second step is to extract the avascular zone from the OCT angiogram using adaptive watershed algorithm 46 combined with an active contour algorithm. Briefly, the original image was first processed with denoising techniques, including Median filtering and Gaussian filtering with 3 × 3 template sizes, and then a region growing algorithm was used to extract the initial FAZ Angi from the denoised image.…”

Section: Methodsmentioning

confidence: 99%

Study of Foveal Avascular Zone Growth in Individuals With Mild Diabetic Retinopathy by Optical Coherence Tomography

Liu,

He,

Kong

et al. 2023

Invest. Ophthalmol. Vis. Sci.

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Purpose The purpose of this study was to investigate the association between foveal vessels and retinal thickness in individuals with diabetic retinopathy (DR) and control subjects, and to reveal foveal avascular zone (FAZ) growth in early individuals with DR. Methods The regions with a thickness less than 60 µm were marked from the intima thickness maps and named FAZ Thic . The avascular zones extracted from the deep vascular plexus were designated as FAZ Angi . The boundary of the two FAZ forms a ring region, which we called FAZ Ring . The FAZ growth rate was defined as the ratio of the FAZ Ring area to the FAZ Thic area. Thirty healthy controls and 30 individuals with mild nonproliferative DR were recruited for this study. Results The FAZ Thic area in individuals with mild DR and control subjects showed similar distribution. The FAZ Angi area in individuals with mild DR are higher than that in control subjects on the whole, but there was no significant difference ( P > 0.05). The FAZ Ring area in individuals with mild DR was significantly higher than that in control subjects ( P < 0.001). However, there is still a small amount of overlap data between the two groups. For the FAZ growth rate, the individuals with mild DR were also significantly larger than the control subjects ( P < 0.001). But there were no overlapping data between the two groups. Conclusions The growth of FAZ in individuals with mild DR can be inferred by comparing FAZ Angi with FAZ Thic . This method minimizes the impact of individual variations and helps researchers to understand the progression mechanism of DR more deeply.

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“…The relationship between these OCTA metrics and the presence and severity of DR was analyzed. Similarly, Liu et al [10] entailed a morphological approach for analyzing OCTA images. The research combined region growing, adaptive watershed, and automated seed point identification for FAZ detection.…”

Section: Introductionmentioning

confidence: 99%

DeepVasNet: Retinal Vasculature and FAZ Segmentation in OCTA with EfficientNet-Enhanced U-Net

Raja,

Gopi,

Francis

et al. 2024

Preprint

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The study and analysis of retinal blood vessels and foveal avascular zone (FAZ) are clinically significant as they help in the early diagnosis of several diseases like diabetic retinopathy, glaucoma, neovasculariza-tion, artery or vein occlusion, and age-related macular degeneration. Recently, optical coherence tomography angiography (OCTA) imaging has been used to visualize the retina due to its non-invasive nature and fast imaging. However, manual retinal vasculature and FAZ segmentation are tedious and time-consuming. In this context, we propose an automated deep-learning-based segmentation method. The traditional U-Net is modified with a pre-trained EfficientNet-B0 in the encoder and a combined spatial, channel attention, squeeze, and excitation mechanism in the decoder. The proposed algorithm is validated on the publicly available OCTA-500 database. Mean Dice coefficients of 88.38, 88.40, 88.48, and 94.55 are obtained for capillary, artery, vein, and FAZ segmenta-tion in the OCTA 6 mm dataset. Whereas mean Dice scores of 90.48, 90.70, 89.59, and 97.98 are reported in the OCTA 3 mm subset for capillary , artery, vein, and FAZ segmentation, respectively. This segmentation performance is superior to other recent methods in the state-of-the-art literature. Overall, the contributions of our work are summarized as DRL-ASOCT follows. The proposed architecture is simple, easy to implement, and requires less memory and time than other networks. Further, we separately segment the retinal vessels (arteries, veins, and capillaries) and achieve improved segmentation accuracy relative to other approaches.

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Automatic segmentation of foveal avascular zone based on adaptive watershed algorithm in retinal optical coherence tomography angiography images

Cited by 11 publications

References 24 publications

A Reliable Criterion for the Correct Delimitation of the Foveal Avascular Zone in Diabetic Patients

A Reliable Criterion for the Correct Delimitation of the Foveal Avascular Zone in Diabetic Patients

Study of Foveal Avascular Zone Growth in Individuals With Mild Diabetic Retinopathy by Optical Coherence Tomography

DeepVasNet: Retinal Vasculature and FAZ Segmentation in OCTA with EfficientNet-Enhanced U-Net

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