Literature DB >> 8849460

Determination of ocular torsion by means of automatic pattern recognition.

E Groen1, J E Bos, P F Nacken, B de Graaf.   

Abstract

A new, automatic method for determination of human ocular torsion (OT) was developed based on the tracking of iris patterns in digitized video images. Instead of quantifying OT by means of cross-correlation of circular iris samples, a procedure commonly applied, this new method automatically selects and recovers a set of 36 significant patterns in the iris by the technique of template matching as described by In den Haak et al. Each relocated landmark results in a single estimate of the torsion angle. A robust algorithm estimates OT from this total set of individually determined torsion angles, thereby largely correcting for errors which may arise due to misjudgement of the rotation center. The new method reproduced OT in a prepared set of images of an artificial eye with an accuracy of 0.1 degree. In a sample of 256 images of human eyes, a practical reliability of 0.25 degrees was achieved. To illustrate the method's usefulness, an experiment is described in which ocular torsion was measured during two dynamic conditions of whole-body roll, namely during sinusoidally pendular motion about either an earth horizontal or earth vertical axis (that is "with" and "without" otolith stimulation, respectively).

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Year:  1996        PMID: 8849460     DOI: 10.1109/10.488795

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  6 in total

1.  Knowing what the brain is seeing in three dimensions: A novel, noninvasive, sensitive, accurate, and low-noise technique for measuring ocular torsion.

Authors:  Jorge Otero-Millan; Dale C Roberts; Adrian Lasker; David S Zee; Amir Kheradmand
Journal:  J Vis       Date:  2015       Impact factor: 2.240

2.  Velocity storage activity is affected after sustained centrifugation: a relationship with spatial disorientation.

Authors:  Suzanne A E Nooij; Jelte E Bos; Eric L Groen
Journal:  Exp Brain Res       Date:  2008-06-20       Impact factor: 1.972

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

Authors:  Kwang-Keun Oh; Byeong-Yeon Moon; Hyun Gug Cho; Sang-Yeob Kim; Dong-Sik Yu
Journal:  J Int Med Res       Date:  2021-03       Impact factor: 1.671

4.  Measuring torsional eye movements by tracking stable iris features.

Authors:  James K Y Ong; Thomas Haslwanter
Journal:  J Neurosci Methods       Date:  2010-08-11       Impact factor: 2.390

5.  Motion tracking of iris features to detect small eye movements.

Authors:  Aayush K Chaudhary; Jeff B Pelz
Journal:  J Eye Mov Res       Date:  2019-04-05       Impact factor: 0.957

6.  Use of iris pattern recognition to evaluate ocular torsional changes associated with head tilt.

Authors:  Mohamed Hussein; David Coats
Journal:  Ther Adv Ophthalmol       Date:  2018-10-24
  6 in total

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