A Study of Visual Attention in Diagnosing Cerebellar Tumours
Visual attention allows user to select the most relevant
information to ongoing behaviour. This paper presents a study on; i)
the performance of people measurements, ii) accurateness of people
measurement of the peaks that correspond to chemical quantities
from the Magnetic Resonance Spectroscopy (MRS) graphs and iii)
affects of people measurements to the algorithm-based diagnosis.
Participant-s eye-movement was recorded using eye-tracker tool
(Eyelink II). This experiment involves three participants for
examining 20 MRS graphs to estimate the peaks of chemical
quantities which indicate the abnormalities associated with
Cerebellar Tumours (CT). The status of each MRS is verified by
using decision algorithm. Analysis involves determination of
humans-s eye movement pattern in measuring the peak of
spectrograms, scan path and determining the relationship of
distributions of fixation durations with the accuracy of measurement.
In particular, the eye-tracking data revealed which aspects of the
spectrogram received more visual attention and in what order they
were viewed. This preliminary investigation provides a proof of
concept for use of the eye tracking technology as the basis for
expanded CT diagnosis.
[1] Preston K., White, Jr, Hutson T. L., and Hutchinson T. E. (1997)
"Modeling Human Eye Behavior during Mammographic Scanning:
Preliminary results", IEEE Trans. Syst., Man, Cybern. A, Vol. 27(1997),
pp. 494-505.
[2] Beard DV, Johnston RE, Toki O, et al.(1990) "A Study of Radiologists
Viewing Multiple Computed Tomography Examinations using an
Eyetracking Device", J Digit Imaging ; 3:230-7.
[3] Ellis S.M, Hu X.P, Dempere-Marco L., Yang G.Z, Wells AU & Hansell
D.M. (2006) "Thin-section CT of the Lungs: Eye-tracking analysis of
the Visual Approach to Reading Tiled and Stacked Display Formats".
Eur J Radiol, Vol 2006;59(2): pp 257-64.
[4] EyeLink II User Manual version (1/10/2005) ┬® 2002-2005 SR Research
Ltd. http://www.eyelinkinfo.com
[5] Xu, A. (2000) "Eye Tracking Study on Identifying and Analyzing User
Behavior - Eye Movements, Eye Fixation Duration and Patterns - When
Processing Numeric Table Data in Paper or PDF Format", School of
Information and Library Science, UNC-CH, November, 2000.
http://ils.unc.edu/idl/details/AirongXu.pdfW.-K. Chen, Linear Networks
and Systems (Book style). Belmont, CA: Wadsworth, 1993, pp. 123-135.
[6] Brennan P, Silman A (1992) "Statistical Methods for Assessing
Observer Variability in Clinical Measures", BMJ 1992;304:1491-4.
[7] Casali, J.G. and Gaylin, K.B (1988) "Selected Graph Design Variables
in Four Interpretation Tasks: A Microcomputer-based Pilot Study",
Behaviour & Information Technology. 7-1 pp31-49. Taylor and Francis
1988.
[8] Dempere-Marco L., Hu X-P., MacDonald S. L. S., Ellis S. M., Hansell
D. M. and Yang G-Z (2002) "The Use of Visual Search for Knowledge
Gathering in Image Decision Support", IEEE Transactions on Medical
Imaging, Vol. 21(7)(2002), pp. 741-754.
[9] Hu X-P., Dempere-Marco L. and Yang G-Z.(2003) "Hot Spot Detection
Based on Feature Space Representation of Visual Search in Medical
Imaging", Proceedings of the 4th Annual IEEE-EMBS Information
Technology Applications in Biomedicine 2003 (ITAB 2003), pp. 261-
264, 24-26 April 2003.
[10] Hu X-P., Dempere-Marco L. and Yang G-Z. (2003) "Feature Based
Visual Search Analysis in Medical Image Understanding", Proceedings
ECEM12, 20-24 August 2003, Dundee, Scotland, UK.
[11] Itti, L., Koch, C.(2001) "Computational Modeling of Visual Attention",
Nature Reviews Neuroscience, Vol. 2 (March, 2001), No. 3, pp. 194-203,
Mar (2001)
[12] Navalpakkam V. , Arbib M.A & Itti L. (2005) "Attention and Scene
Understanding" Neurobiology of Attention, pp. 197-203, San Diego,
CA:Elsevier, 2005.
[1] Preston K., White, Jr, Hutson T. L., and Hutchinson T. E. (1997)
"Modeling Human Eye Behavior during Mammographic Scanning:
Preliminary results", IEEE Trans. Syst., Man, Cybern. A, Vol. 27(1997),
pp. 494-505.
[2] Beard DV, Johnston RE, Toki O, et al.(1990) "A Study of Radiologists
Viewing Multiple Computed Tomography Examinations using an
Eyetracking Device", J Digit Imaging ; 3:230-7.
[3] Ellis S.M, Hu X.P, Dempere-Marco L., Yang G.Z, Wells AU & Hansell
D.M. (2006) "Thin-section CT of the Lungs: Eye-tracking analysis of
the Visual Approach to Reading Tiled and Stacked Display Formats".
Eur J Radiol, Vol 2006;59(2): pp 257-64.
[4] EyeLink II User Manual version (1/10/2005) ┬® 2002-2005 SR Research
Ltd. http://www.eyelinkinfo.com
[5] Xu, A. (2000) "Eye Tracking Study on Identifying and Analyzing User
Behavior - Eye Movements, Eye Fixation Duration and Patterns - When
Processing Numeric Table Data in Paper or PDF Format", School of
Information and Library Science, UNC-CH, November, 2000.
http://ils.unc.edu/idl/details/AirongXu.pdfW.-K. Chen, Linear Networks
and Systems (Book style). Belmont, CA: Wadsworth, 1993, pp. 123-135.
[6] Brennan P, Silman A (1992) "Statistical Methods for Assessing
Observer Variability in Clinical Measures", BMJ 1992;304:1491-4.
[7] Casali, J.G. and Gaylin, K.B (1988) "Selected Graph Design Variables
in Four Interpretation Tasks: A Microcomputer-based Pilot Study",
Behaviour & Information Technology. 7-1 pp31-49. Taylor and Francis
1988.
[8] Dempere-Marco L., Hu X-P., MacDonald S. L. S., Ellis S. M., Hansell
D. M. and Yang G-Z (2002) "The Use of Visual Search for Knowledge
Gathering in Image Decision Support", IEEE Transactions on Medical
Imaging, Vol. 21(7)(2002), pp. 741-754.
[9] Hu X-P., Dempere-Marco L. and Yang G-Z.(2003) "Hot Spot Detection
Based on Feature Space Representation of Visual Search in Medical
Imaging", Proceedings of the 4th Annual IEEE-EMBS Information
Technology Applications in Biomedicine 2003 (ITAB 2003), pp. 261-
264, 24-26 April 2003.
[10] Hu X-P., Dempere-Marco L. and Yang G-Z. (2003) "Feature Based
Visual Search Analysis in Medical Image Understanding", Proceedings
ECEM12, 20-24 August 2003, Dundee, Scotland, UK.
[11] Itti, L., Koch, C.(2001) "Computational Modeling of Visual Attention",
Nature Reviews Neuroscience, Vol. 2 (March, 2001), No. 3, pp. 194-203,
Mar (2001)
[12] Navalpakkam V. , Arbib M.A & Itti L. (2005) "Attention and Scene
Understanding" Neurobiology of Attention, pp. 197-203, San Diego,
CA:Elsevier, 2005.
@article{"International Journal of Medical, Medicine and Health Sciences:62228", author = "Kuryati Kipli and Kasumawati Lias and Dayang Azra Awang Mat and Al-Khalid Othman and Ade Syaheda Wani Marzuki and Nurdiani Zamhari", title = "A Study of Visual Attention in Diagnosing Cerebellar Tumours", abstract = "Visual attention allows user to select the most relevant
information to ongoing behaviour. This paper presents a study on; i)
the performance of people measurements, ii) accurateness of people
measurement of the peaks that correspond to chemical quantities
from the Magnetic Resonance Spectroscopy (MRS) graphs and iii)
affects of people measurements to the algorithm-based diagnosis.
Participant-s eye-movement was recorded using eye-tracker tool
(Eyelink II). This experiment involves three participants for
examining 20 MRS graphs to estimate the peaks of chemical
quantities which indicate the abnormalities associated with
Cerebellar Tumours (CT). The status of each MRS is verified by
using decision algorithm. Analysis involves determination of
humans-s eye movement pattern in measuring the peak of
spectrograms, scan path and determining the relationship of
distributions of fixation durations with the accuracy of measurement.
In particular, the eye-tracking data revealed which aspects of the
spectrogram received more visual attention and in what order they
were viewed. This preliminary investigation provides a proof of
concept for use of the eye tracking technology as the basis for
expanded CT diagnosis.", keywords = "eye tracking, fixation durations, pattern, scan paths, spectrograms, visual.", volume = "3", number = "11", pages = "348-5", }