Measuring torsional eye movements by tracking stable iris features

Ong, James K Y; Haslwanter, Thomas

doi:10.1016/j.jneumeth.2010.08.004

Cited by 34 publications

(25 citation statements)

References 23 publications

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“… 25 In addition, during measurement of OCR values, iris images reportedly could replace FIs. Previous studies that measured OCR values using iris images 25 , 34 reported that OCR measurement did not significantly differ between iris images and FIs; a strong correlation was observed between the two methods. Unlike previously described methods that lacked investigations of binocular fixation, our method used binocular fixation and a correlation analysis among the mean OCR values measured by the four methods (CPC, PC, PP, and FI); our findings showed positive correlations in all head tilt conditions.…”

Section: Discussionmentioning

confidence: 73%

Measurement of ocular counter-roll using iris images during binocular fixation and head tilt

Moon

Cho

et al. 2021

J Int Med Res

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Objective To compare the ocular counter-roll (OCR) measured using iris images during binocular fixation and head tilt with OCR measured via fundus photography. Methods Fifty-three healthy college students participated in this study. The mean OCR was measured by collection of iris images and fundus images under seven head tilt conditions (0 degrees; 10, 20, and 30 degrees right; and 10, 20, and 30 degrees left). Three iris images (crossed pupil center, pupil center, and pupil periphery) were taken using a slit-lamp biomicroscope with an ophthalmic camera and a half-silvered mirror; fundus images were collected via fundus photography. The mean OCR values were compared between images taken with each method. Results No iris images or head tilt conditions revealed any significant differences in mean OCR comparison with fundus images. The mean difference in OCR was smallest, and the correlation was greatest, between the crossed pupil center and fundus images. Conclusion A half-silvered mirror and iris images can replace fundus photography for the measurement of OCR.

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Section: Discussionmentioning

confidence: 73%

Measurement of ocular counter-roll using iris images during binocular fixation and head tilt

Moon

Cho

et al. 2021

J Int Med Res

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“…Parsa and Kumar recently suggested that rotation of the retinal vascular arcades provides landmarks for use as an accessory sign of ocular torsion [ 23 ]. Real-time iris registration as used in refractive surgery can also be used to assess ocular torsion, but this is expensive, time-consuming, and less accurate than fundus photographic methods [ 24 ].…”

Section: Discussionmentioning

confidence: 99%

Measuring ocular torsion and its variations using different nonmydriatic fundus photographic methods

et al. 2020

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Purpose To compare the variations in ocular torsion measurements made using different fundus photographic methods. Methods We enrolled subjects with three conditions: (1) patients with intermittent exotropia (IXT) (n = 44), (2) patients with unilateral superior oblique palsy (SOP) (n = 10), and (3) normal subjects as controls (n = 85). Ocular torsion was measured by disc-center–fovea angle (DFA) using three different imaging modalities: (1) conventional fundus photography (CFP) with a 45° field of view (FV), (2) wide-field fundus photography (WFP) with a 200° FV, and (3) optical coherence tomography (OCT) with a 55° FV. Results In the IXT group, the DFAs in the right and left eyes were 5.70±3.35° and 6.37±3.36°, respectively, for CFP, 8.39±5.24° and 8.61±3.67° for WFP, and 5.73±3.61° for 6.16±3.50° for OCT. In the SOP group, the DFAs in paretic and nonparetic eyes were 12.19±1.69° and 6.71±1.09°, respectively, for CFP, 14.29±2.36° and 8.23±3.31° for WFP, and 12.12±1.73° and 6.91±1.12° for OCT. In the control group, the DFAs in the right and left eyes were 5.39±2.65° and 5.71±3.16°, respectively, for CFP, 8.77±5.56° and 8.90±6.24° for WFP, and 5.27±2.67° and 5.72±3.20° for OCT. There was no difference between the results from CFP and OCT among the three groups. However, the torsional angle was larger when measured using WFP than the other two photographic methods (CFP and OCT) in all three groups (all p<0.05). Conclusion The ocular torsion measurement varies with the fundus photographic method used to measure it. Clinicians should be careful to avoid overestimating ocular extorsion when it is evaluated using WFP.

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“…If a pupil was found, edge-detection and ellipse-fitting algorithms were used to localize the center of the pupil. The directions of the horizontal and vertical movements were determined by the sum of the transient velocity, as previously described [14,16,17]. The center of the pupil in the first frame of each video clip was used as the reference.…”

Section: Methodsmentioning

confidence: 99%

Developing a Diagnostic Decision Support System for Benign Paroxysmal Positional Vertigo Using a Deep-Learning Model

Lim

Park

Jeon

et al. 2019

JCM

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Background: Diagnosis of benign paroxysmal positional vertigo (BPPV) depends on the accurate interpretation of nystagmus induced by positional tests. However, difficulties in interpreting eye-movement often can arise in primary care practice or emergency room. We hypothesized that the use of machine learning would be helpful for the interpretation. Methods: From our clinical data warehouse, 91,778 nystagmus videos from 3467 patients with dizziness were obtained, in which the three-dimensional movement of nystagmus was annotated by four otologic experts. From each labeled video, 30 features changed into 255 grid images fed into the input layer of the neural network for the training dataset. For the model validation, video dataset of 3566 horizontal, 2068 vertical, and 720 torsional movements from 1005 patients with BPPV were collected. Results: The model had a sensitivity and specificity of 0.910 ± 0.036 and 0.919 ± 0.032 for horizontal nystagmus; of 0.879 ± 0.029 and 0.894 ± 0.025 for vertical nystagmus; and of 0.783 ± 0.040 and 0.799 ± 0.038 for torsional nystagmus, respectively. The affected canal was predicted with a sensitivity of 0.806 ± 0.010 and a specificity of 0.971 ± 0.003. Conclusions: As our deep-learning model had high sensitivity and specificity for the classification of nystagmus and localization of affected canal in patients with BPPV, it may have wide clinical applicability.

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Measuring torsional eye movements by tracking stable iris features

Abstract: Research highlights▶ Maximally Stable Volumes are automatically detected features. ▶ Maximally Stable Volumes allow stable tracking through time. ▶ Robust to nonuniform illumination and large changes in eye position. ▶ Faster than cross-correlation.

Cited by 34 publications

References 23 publications

Measurement of ocular counter-roll using iris images during binocular fixation and head tilt

Measurement of ocular counter-roll using iris images during binocular fixation and head tilt

Measuring ocular torsion and its variations using different nonmydriatic fundus photographic methods

Developing a Diagnostic Decision Support System for Benign Paroxysmal Positional Vertigo Using a Deep-Learning Model

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