Computerized mouse pupil size measurement for pupillary light reflex analysis

Computer Methods and Programs in Biomedicine

Volumn 90, Issue 3, 2008, Pages 202-209

  Lu, Wei ^a   Tan, Jinglu ^a   Zhang, Keqing ^a,b   Lei, Bo ^a,b  

^a UNIVERSITY OF MISSOURI   (United States)

^b University of Missouri   (United States)

Author keywords

Image processing; Infrared; Object detection; Pupil size; Pupillary light reflex; Randomized Hough transform

Indexed keywords

DIAGNOSIS; ELECTRONIC DOCUMENT IDENTIFICATION SYSTEMS; INFRARED IMAGING; OBJECT RECOGNITION;

AUTOMATED PUPIL DETECTION; PUPILLARY LIGHT REFLEX (PLR);

BIOMEDICAL ENGINEERING;

ACCURACY; ALGORITHM; ANIMAL EXPERIMENT; ARTICLE; ARTIFACT; AUTOMATION; COMPUTER SYSTEM; CORNEA; IRIS; MEASUREMENT; MOUSE; NONHUMAN; PUPIL REFLEX; RELIABILITY;

ALGORITHMS; ANIMALS; DIAGNOSIS, COMPUTER-ASSISTED; IMAGE PROCESSING, COMPUTER-ASSISTED; MICE; MICE, INBRED C57BL; PUPIL; REFLEX, PUPILLARY; RETINAL DEGENERATION; SOFTWARE DESIGN;

EID: 42249090880     PISSN: 01692607     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cmpb.2008.01.002     Document Type: Article

References (27)

1. Lucas R.J., Douglas R.H., and Foster R.G. Characterization of an ocular photopigment capable of driving pupillary constriction in mice. Nat. Neurosci. 4 (2001) 621-626
2. Lucas R.J., Hattar S., Takao M., Berson D.M., Foster R.G., and Yau K.W. Diminished pupillary light reflex at high irradiances in melanopsin-knockout mice. Science 299 (2003) 245-247
3. Pennesi M.E., Lyubarsky A.L., and Pugh Jr. E.N. Extreme responsiveness of the pupil of the dark-adapted mouse to steady retinal illumination. Invest. Ophthalmol. Vis. Sci. 39 (1998) 2148-2156
4. O'Neill W.D., and Trick K.P. The narcoleptic cognitive pupillary response. IEEE Trans. Biomed. Eng. 48 (2001) 963-968
5. O'Neill W.D., Oroujeh A.M., and Merritt S.L. Pupil noise is a discriminator between narcoleptics and controls. IEEE Trans Biomed. Eng. 45 (1998) 314-322
6. Van Gelder R.N., Wee R., Lee J.A., and Tu D.C. Reduced pupillary light responses in mice lacking cryptochromes. Science 299 (2003) 222
7. Aleman T.S., Jacobson S.G., Chico J.D., Scott M.L., Cheung A.Y., Windsor E.A., Furushima M., Redmond T.M., Bennett J., Palczewski K., and Cideciyan A.V. Impairment of the transient pupillary light reflex in rpe65(-/-) mice and humans with leber congenital amaurosis. Invest. Ophthalmol. Vis. Sci. 45 (2004) 1259-1271
8. Sakatani T., and Isa T. Pc-based high-speed video-oculography for measuring rapid eye movements in mice. Neurosci. Res. 49 (2004) 123-131
9. Murray R.B., and Loughnane M.H. Infrared video pupillometry: a method used to measure the pupillary effects of drugs in small laboratory animals in real time. J. Neurosci. Methods 3 (1981) 365-375
10. Nguyen A.H., and Stark L.W. Model control of image processing: pupillometry. Comput. Med. Imaging Graph 17 (1993) 21-33
11. Moore S.T., Curthoys I.S., and McCoy S.G. Vtm-an image-processing system for measuring ocular torsion. Comput. Methods Programs Biomed. 35 (1991) 219-230
12. Zhu D., Moore S.T., and Raphan T. Robust pupil center detection using a curvature algorithm. Comput. Methods Programs Biomed. 59 (1999) 145-157
13. Clarke A.H., Teiwes W., and Scherer H. Video-oculography-an alternative method for measurement of three-dimensional eye movements. In: Schmid R., and Zambarbieri D. (Eds). Oculomotor Control and Cognitive Processes (1991), Elsevier, New York, NY
14. Mulligan J.B. Image processing for improved eye-tracking accuracy. Behav. Res. Methods Instrum. Comput. 29 (1997) 54-65
15. Groen E., Bos J.E., Nacken P.F., and de Graaf B. Determination of ocular torsion by means of automatic pattern recognition. IEEE Trans. Biomed. Eng. 43 (1996) 471-479
16. Zhu D., Moore S.T., and Raphan T. Robust and real-time torsional eye position calculation using a template-matching technique. Comput. Methods Programs Biomed. 74 (2004) 201-209
17. Wingate M., Hood B., Shi H., and Phan P. Automated pupil size determination for evaluating fluctuations in physiological arousal. Proceedings of the ICSP' 98 (1998)
18. Lu W., and Tan J. Detection of incomplete ellipse in images with strong noise by iterative randomized Hough transform (IRHT). Pattern Recogn. 41 (2008) 1268-1279
19. Zhang C., Lei B., Lam T.T., Yang F., Sinha D., and Tso M.O. Neuroprotection of photoreceptors by minocycline in light-induced retinal degeneration. Invest. Ophthalmol. Vis. Sci. 45 (2004) 2753-2759
20. Lei B. The erg of guinea pig (cavis porcellus): comparison with i-type monkey and e-type rat. Doc. Ophthalmol. 106 (2003) 243-249
21. Gonzalez R.C., and Woods R.E. Digital Image Processing (1992), Addison-Wesley, Reading, MA
22. Lu W., Tan J., and Floyd R. Automated fetal head detection and measurement in ultrasound images by iterative randomized Hough transform. Ultrasound Med. Biol. 31 (2005) 929-936
23. Leavers V.F. The dynamic generalized Hough transform: its relationship to the probabilistic Hough transforms and an application to the concurrent detection of circles and ellipses. Computer Vision Graph. Image Process.: Image Und. 56 (1992) 381-398
24. Forbes A.B. Fitting an Ellipse to Data Technical Report DITC 95/87 (1987), National Physical Laboratory, Teddington, UK
25. Matsuda K., and Nagami T. All purpose measurement system of the eye positions. Proceedings of the 12th Symposium on Biological and Physiological Engineering. Machida, Japan (1998)
26. Deter R.L., Harrist R.B., Hadlock F.P., and Carpenter R.J. Fetal head and abdominal circumferences. I. Evaluation of measurement errors. J. Clin. Ultrasound 10 (1982) 357-363
27. Bland J.M., and Altman D.G. Measuring agreement in method comparison studies. Stat. Methods Med. Res. 8 (1999) 135-160