Abstract
To explore the impact of different image registration algorithms on the diagnosis of visual path damage in patients with primary open angle glaucoma (POAG), 60 cases of suspected POAG patients were selected as the research objects. Shape-preserving scale invariant feature transform (SP-SIFT) algorithm, scale invariant feature transform (SIFT) algorithm, and Kanade-Lucas-Tomasi (KLT) algorithm were compared and applied to MRI images of 60 POAG patients. It was found that the SP-SIFT algorithm converged after 33 iterations, which had a higher registration speed than the SIFT algorithm and the KLT algorithm. The mean errors of the SP-SIFT algorithm in the rotation angle, X-direction translation, and Y-direction translation were 2.11%, 4.56%, and 4.31%, respectively. Those of the SIFT algorithm were 5.55%, 9.98%, and 7.01%, respectively. Those of the KLT algorithm were 7.45%, 11.31%, and 8.56%, respectively, and the difference among algorithms was significant ( P < 0.05 ). The diagnostic sensitivity and accuracy of the SP-SIFT algorithm for POAG were 96.15% and 94.34%, respectively. Those of the SIFT algorithm were 94.68% and 90.74%, respectively. Those of the KLT algorithm were 94.21% and 90.57%, respectively, and the three algorithms had significant differences ( P < 0.05 ). The results of MRI images based on the SP-SIFT algorithm showed that the average thickness of the cortex of the patient’s left talar sulcus, right talar sulcus, left middle temporal gyrus, and left fusiform gyrus were 2.49 ± 0.15 mm, 2.62 ± 0.13 mm, 3.00 ± 0.10 mm, and 2.99 ± 0.17 mm, respectively. Those of the SIFT algorithm were 2.51 ± 0.17 mm, 2.69 ± 0.12 mm, 3.11 ± 0.13 mm, and 3.09 ± 0.14 mm, respectively. Those of the KLT algorithm were 2.35 ± 0.12 mm, 2.52 ± 0.16 mm, 2.77 ± 0.11 mm, and 2.87 ± 0.17 mm, respectively, and the three algorithms had significant differences ( P < 0.05 ). In summary, the SP-SIFT algorithm was ideal for POAG visual pathway diagnosis and was of great adoption potential in clinical diagnosis.
Highlights
Glaucoma is a disease characterized by visual field defects and sunken optic nerve atrophy, which can cause serious damage to the patient’s visual function
Registration Accuracy Comparison. e 19th slice of the 32nd magnetic resonance imaging (MRI) image of the experimental group was randomly selected for analysis
In terms of convergence speed, since the SPSIFT algorithm first denoised the image and enhances the contrast, it converged after 33 iterations, which had a higher registration speed than the scale invariant feature transform (SIFT) algorithm and the KLT algorithm
Summary
Glaucoma is a disease characterized by visual field defects and sunken optic nerve atrophy, which can cause serious damage to the patient’s visual function. The incidence of glaucoma ranks second, second only to cataracts [1]. Among glaucoma patients in China, primary glaucoma accounts for about 87% of the total number of patients, and it mostly occurs in the adult population. Glaucoma has caused a great threat to people’s vision health. According to the shape of the patient’s chamber angle, primary glaucoma is classified into primary angle closure glaucoma (PACG) and POAG [2]. E onset of POAG is relatively slow. The patient’s retinal nerve fiber layer and optic nerve have already been damaged
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