Investigation on Non-Segmentation Based Algorithms for Microvasculature Quantification in OCTA Images
Optical Coherence Tomography Angiography (OCTA) is an imaging modality that provides threedimensional information of the retinal microvasculature and therefore promises early diagnosis and sufficient monitoring in ophthalmology. However, there is considerable variability between experts analysing th...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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De Gruyter
2021-10-01
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| Series: | Current Directions in Biomedical Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/cdbme-2021-2063 |
| _version_ | 1811324243577667584 |
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| author | Abuzer Amr Naber Ady Hoffmann Simon Kessler Lucy Khoramnia Ramin Nahm Werner |
| author_facet | Abuzer Amr Naber Ady Hoffmann Simon Kessler Lucy Khoramnia Ramin Nahm Werner |
| author_sort | Abuzer Amr |
| collection | DOAJ |
| description | Optical Coherence Tomography Angiography (OCTA) is an imaging modality that provides threedimensional information of the retinal microvasculature and therefore promises early diagnosis and sufficient monitoring in ophthalmology. However, there is considerable variability between experts analysing this data. Measures for quantitative assessment of the vasculature need to be developed and established, such as fractal dimension. Fractal dimension can be used to assess the complexity of vessels and has been shown to be independently associated with neovascularization, a symptom of diseases such as diabetic retinopathy. This investigation assessed the performance of three fractal dimension algorithms: Box Counting Dimension (BCD), Information Dimension (ID), and Differential Box Counting (DBC). Two of those, BCD and ID, rely on previous vessel segmentation. Assessment of the added value or disturbance regarding the segmentation step is a second aim of this study. The investigation was performed on a data set composed of 9 in vivo human eyes. Since there is no ground truth available, the performance of the methods in differentiating the Superficial Vascular Complex (SVC) and Deep Vascular Complex (DVC) layers apart and the consistency of measurements of the same layer at different time-points were tested. The performance parameters were the ICC and the Mann- Whitney U tests. The three applied methods were suitable to tell the different layers apart and showed consistent values applied in the same slab. Within the consistency test, the non-segmentation-based method, DBC, was found to be less accurate, expressed in a lower ICC value, compared to its segmentation-based counterparts. This result is thought to be due to the DBC’s higher sensitivity when compared to the other methods. This higher sensitivity might help detect changes in the microvasculature, like neovascularization, but is also more likely prone to noise and artefacts. |
| first_indexed | 2024-04-13T14:10:54Z |
| format | Article |
| id | doaj.art-46b79b9d94ea446580bdb68a0e89d9a6 |
| institution | Directory Open Access Journal |
| issn | 2364-5504 |
| language | English |
| last_indexed | 2024-04-13T14:10:54Z |
| publishDate | 2021-10-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Current Directions in Biomedical Engineering |
| spelling | doaj.art-46b79b9d94ea446580bdb68a0e89d9a62022-12-22T02:43:48ZengDe GruyterCurrent Directions in Biomedical Engineering2364-55042021-10-017224725010.1515/cdbme-2021-2063Investigation on Non-Segmentation Based Algorithms for Microvasculature Quantification in OCTA ImagesAbuzer Amr0Naber Ady1Hoffmann Simon2Kessler Lucy3Khoramnia Ramin4Nahm Werner5Institute of Biomedical Engineering, Karlsruhe Institute of Technology,Karlsruhe, GermanyInstitute of Biomedical Engineering, Karlsruhe Institute of Technology,Karlsruhe, GermanyInstitute of Biomedical Engineering, Karlsruhe Institute of Technology,Karlsruhe, GermanyEye Clinic, University Hospital Heidelberg,Heidelberg, GermanyUniversitätsklinikum,Heidelberg, GermanyInstitute of Biomedical Engineering, Karlsruhe Institute of Technology,Karlsruhe, GermanyOptical Coherence Tomography Angiography (OCTA) is an imaging modality that provides threedimensional information of the retinal microvasculature and therefore promises early diagnosis and sufficient monitoring in ophthalmology. However, there is considerable variability between experts analysing this data. Measures for quantitative assessment of the vasculature need to be developed and established, such as fractal dimension. Fractal dimension can be used to assess the complexity of vessels and has been shown to be independently associated with neovascularization, a symptom of diseases such as diabetic retinopathy. This investigation assessed the performance of three fractal dimension algorithms: Box Counting Dimension (BCD), Information Dimension (ID), and Differential Box Counting (DBC). Two of those, BCD and ID, rely on previous vessel segmentation. Assessment of the added value or disturbance regarding the segmentation step is a second aim of this study. The investigation was performed on a data set composed of 9 in vivo human eyes. Since there is no ground truth available, the performance of the methods in differentiating the Superficial Vascular Complex (SVC) and Deep Vascular Complex (DVC) layers apart and the consistency of measurements of the same layer at different time-points were tested. The performance parameters were the ICC and the Mann- Whitney U tests. The three applied methods were suitable to tell the different layers apart and showed consistent values applied in the same slab. Within the consistency test, the non-segmentation-based method, DBC, was found to be less accurate, expressed in a lower ICC value, compared to its segmentation-based counterparts. This result is thought to be due to the DBC’s higher sensitivity when compared to the other methods. This higher sensitivity might help detect changes in the microvasculature, like neovascularization, but is also more likely prone to noise and artefacts.https://doi.org/10.1515/cdbme-2021-2063differential box countingocta imagesfractal dimensions. |
| spellingShingle | Abuzer Amr Naber Ady Hoffmann Simon Kessler Lucy Khoramnia Ramin Nahm Werner Investigation on Non-Segmentation Based Algorithms for Microvasculature Quantification in OCTA Images Current Directions in Biomedical Engineering differential box counting octa images fractal dimensions. |
| title | Investigation on Non-Segmentation Based Algorithms for Microvasculature Quantification in OCTA Images |
| title_full | Investigation on Non-Segmentation Based Algorithms for Microvasculature Quantification in OCTA Images |
| title_fullStr | Investigation on Non-Segmentation Based Algorithms for Microvasculature Quantification in OCTA Images |
| title_full_unstemmed | Investigation on Non-Segmentation Based Algorithms for Microvasculature Quantification in OCTA Images |
| title_short | Investigation on Non-Segmentation Based Algorithms for Microvasculature Quantification in OCTA Images |
| title_sort | investigation on non segmentation based algorithms for microvasculature quantification in octa images |
| topic | differential box counting octa images fractal dimensions. |
| url | https://doi.org/10.1515/cdbme-2021-2063 |
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