Automated Registration of Multimodal Optic Disc Images
| Autor: | Wai Siene Ng, Paul L. Rosin, Kyaw Aye, Venkat Avadhanam, Steffan H. P. Evans, Andrew David Marshall, Philip A. Legg, James Edwards Morgan, Rachel Valerie North |
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| Rok vydání: | 2016 |
| Předmět: |
Diagnostic Imaging
Computer science Optic Disk QA76 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Image Interpretation Computer-Assisted Optic Nerve Diseases Photography medicine Humans Computer vision Intraocular Pressure Heidelberg retina tomograph medicine.diagnostic_test business.industry Fundus photography Reproducibility of Results Glaucoma Mutual information Image Enhancement Ophthalmology medicine.anatomical_structure Feature (computer vision) 030221 ophthalmology & optometry RE Artificial intelligence Tomography business Algorithms Grading scale Optic disc |
| Zdroj: | Journal of Glaucoma. 25:397-402 |
| ISSN: | 1057-0829 |
| DOI: | 10.1097/ijg.0000000000000252 |
| Popis: | Purpose: To determine the accuracy of automated alignment algorithms for the registration of optic disc images obtained by 2 different modalities: fundus photography and scanning laser tomography.\ud \ud Materials and Methods: Images obtained with the Heidelberg Retina Tomograph II and paired photographic optic disc images of 135 eyes were analyzed. Three state-of-the-art automated registration techniques Regional Mutual Information, rigid Feature Neighbourhood Mutual Information (FNMI), and nonrigid FNMI (NRFNMI) were used to align these image pairs. Alignment of each composite picture was assessed on a 5-point grading scale: “Fail” (no alignment of vessels with no vessel contact), “Weak” (vessels have slight contact), “Good” (vessels with 50% contact), and “Excellent” (complete alignment). Custom software generated an image mosaic in which the modalities were interleaved as a series of alternate 5×5-pixel blocks. These were graded independently by 3 clinically experienced observers.\ud \ud Results: A total of 810 image pairs were assessed. All 3 registration techniques achieved a score of “Good” or better in >95% of the image sets. NRFNMI had the highest percentage of “Excellent” (mean: 99.6%; range, 95.2% to 99.6%), followed by Regional Mutual Information (mean: 81.6%; range, 86.3% to 78.5%) and FNMI (mean: 73.1%; range, 85.2% to 54.4%).\ud \ud Conclusions: Automated registration of optic disc images by different modalities is a feasible option for clinical application. All 3 methods provided useful levels of alignment, but the NRFNMI technique consistently outperformed the others and is recommended as a practical approach to the automated registration of multimodal disc images. |
| Databáze: | OpenAIRE |
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