Basic Research for Distinguishing Small Retinal Hemorrhages from Dust Artifact by using Hue, Lightness, and Saturation Color Space
To distinguish small retinal hemorrhages in early
diabetic retinopathy from dust artifacts, we analyzed hue, lightness,
and saturation (HLS) color spaces. The fundus of 5 patients with
diabetic retinopathy was photographed. For the initial experiment, we
placed 4 different colored papers on the ceiling of a darkroom. Using
each color, 10 fragments of house dust particles on a magnifier were
photographed. The colored papers were removed, and 3 different
colored light bulbs were suspended from the ceiling. Ten fragments of
house dust particles on the camera-s object lens were photographed.
We then constructed an experimental device that can photograph
artificial eyes. Five fragments of house dust particles under the ocher
fundus of the artificial eye were photographed. On analyzing HLS
color space of the dust artifact, lightness and saturation were found to
be highly sensitive. However, hue was not highly sensitive.
[1] O. T. Tsuchiya., Measure Against Lifestyle Related Disease, JMAJ,
Vol.49 no.3, 2006, pp132-134.
[2] E. Duh, Diabetic Retinopathy, Humana Press, 2008, pp29-66
[3] American Diabetes Association, Diabetic retinopathy, Clinical Diabetes,
Vol. 19, No. 1, 2001, pp29-32
[4] S. S. Savant and H. B. Chandalia, Diabetic retinopathy, Intnl. J. Dev.
Contries, Vol. 10, 1991, pp,9-25
[5] J. B. Brown, K. L. Pedula, K. H. Summers, Diabetic retinopathy,
Diabetes Care, Vol. 26, No. 9, 2003, pp2637-2642.
[6] S. Garg and R. M. Davis, Diabetic retinopathy screening update, Clinical
diabetes, Vo. 27, No. 4, 2009, pp140-145.
[7] I. U. Scott, N. M. Bressler, S. B. Bresseler et al, Agreement between
clinical and reading center gradings of diabetic retinopathy severity level
at baseline in a phase 2 study of intravitreal bevacizumab for diabetic
macular edema, Retina, Vol. 28, No. 1, 2008, pp36-40.
[8] M. S. Figueroa, I . Contreras, S. Noval, Anti-angiogetic drugs as an
adjunctive therapy in the surgical treatment of diabetic retinopathy, Curr
Diabetes Rev., Vol. 5, No. 1, 2009, pp52-56.
[9] A.G. Oomen, J. P. C. M. Janssen, A. Dusseldorp et al., Ecposure to
chemicals via house dust, RIVM Report 609021064/2008, 2008,
pp11-18.
[10] E. Fernández-Caldas, W. L. Trudeau and D. K. Ledford, Environmental
control of indoor biologic agents. J. Allergy. Clin. Immunol., issue 2, part
2, 1994, pp404-412.
[11] R. G. Willson, M. W. Maimone, A. E. Johnson et al, An Optical Model for
Image Artifacts Produced by Dust Particles on Lenses, Proc. ISAIRAS
2005 Conference, 2005, ESA SP p603.
[12] A.V. Shukla, Clinical Optics Primer for Ophthalmic Medical Personnel,
A Guide to Laws, Formulae, Calculations, and Clinical Applications,
SLACK Inc. 2009, pp85-89.
[13] M. Born and E. Wolf, Principles of Optics 7th expanded edition,
Electromagnetic Theory of Propagation, Interference and Diffraction of
Light, Cambridge Univ. Press, 1999, pp142-227.
[14] D. D. David, R. Prescott, and S. Kennedy, Simultaneous stereoscopic
fundus camera incorporating a single optical axis, Invest. Ophthalmol.
Vis. Sci. March, 1980, pp289-297.
[15] R. Zeimer, S. Zou, T. Meeder et al, A fundus camera dedicated to the
screening of diabetic retinopathy in the primary-care physician-s office,
IOVS May, Vol. 43, No. 5, 2002, pp1581-1587
[16] M. Niemeijer, B. Ginneken, S. R. Russell et al, Automated detection and
differential of drusen, exudates, and cotton-wool spots in digital color
fundus photographs for diabetic retinopathy diagnosis, Invest.
Ophthalmol. Vis. Sci., Vol. 48, No. 5, 2007, pp2260-2267.
[17] D.Y. Lin, M. S. Blumenkrans, R. J. Brothers et al, The sensitivity and
specificity of single-field nonmydriatic monochromatic digital fundus
photography with remote image interpretation for diabetic retinopathy
screening: a comparison with ophthalmoscopy and standardized
mydriatic color photography, Am. J. Ophthalmol., Vol. 134, 2002,
pp204-213.
[18] J. A. Olson, F. M. Strachan, J. H. Hipwell et al, A comparative evaluation
of digital imaging, retinal photography and optometrist examination in
screening for diabetic retinopathy, Diabet. Med., Vol. 20, 2003,
pp528-534.
[19] A. E. Dirik, H. T. Sencar and N. Memon, Source Camera Identification
Based on Sensor dust Characteristics, Signal Processing Applications for
Public Security and Forensics 2007, SAFE-07, IEEE Workshop, 2007,
pp1-6.
[20] R. Bergman, R. Maurer, H. Nachlieli et al, Comprehensive Solutions for
Removal of Dust and Scratches from Images, Journal of Electronic
Imaging, Vol. 17, No. 1, 2008, pp1-25.
[21] A. Zamfir, A. Drimbarean, M. Zamfir et al., An Optic Model of the
Appearance of Blemishes in Digital Photographs, Proceedings of SPIE,
Vol. 6502, Digital Photography 3, 2007.
[22] A. E. Dirik, H. T. Sencar and N. Memon, Digital Single Lens Reflex
Camera Identification From Traces of Sensor Dust, IEEE Trans. Info. For.
and Sec., Vol. 3, No. 3, 2008, pp539-552.
[23] R. F. Lyon, Prism-Based Color Separation for Professional Digital
Photography, Proceedings of IS&T-s PICS 2000 Conference: Image
Processing, Image Quality, Image Capture Systems Conference, Oregon,
2000, pp50-54.
[24] H. Narasimha-Iyer, A. Can, B. Roysam et al., Robust Detection and
Classification of Longitudinal Changes in Color Retinal Fundus Images
for Monitoring Diabetic Retinopathy, IEEE Trans. Biomed. Eng., Vol.
53, No. 6, 2006, pp1084-1098.
[25] H. Narasima-lyer, A. Can, B. Roysam et al, Integrated analysis of vascular
and nonvascular changes from color retinal fundus image sequences.,
IEEE Trans Biomed Eng., Vol. 54, No. 8, 2007, pp1436-45.
[26] P. J. Saine, Errors in Fundus Photography, Journal of Ophthalmic
Photography, Vol. 7, No. 2, 1984, pp120-122.
[27] M. Tkalˇciˇc & F. J. Tasiˇc, Colour spaces - perceptual , historical and
applicational background, EUROCON 2003, Computer as a tool, The
IEEE Region 8, Vol.1, 2003, pp304-308.
[28] J. Koenderink, Colour for the sciences, The MIT Press, 2009, pp45-52,
pp497-537.
[29] B. Jahne, Practical Handbook on Image Processing for Scientific
Applications, CRC Press, 1997, pp102-107.
[30] B. G. Haskell, A. Puri and A. N. Netravali, Digital Video: An Introduction
to MPEG-2, Chapman & Hall, 1997, pp86-91.
[31] A. Hanbury and J. Serra, Mathematical Morphology in the HLS Colour
Space, 12th British Machine Vision Conference, Manchester, UK, 2001,
pp 451-460.
[32] Jasc Software, Inc., Chapter 8: Making color and Tonal Corrections, Paint
Shop Pro 8 User Guide, 2002, pp181-206.
[33] R. A. Peters II, Mathematical morphology for angle-valued images,
Proceedings of the SPIE, Nonlinear Image Processing VIII 3026, 1997,
pp84-94.
[34] Nikon Corporations, Nikon D1X Operators Manual, pp212-219.
[35] FUJIFILM Corporation, Digital Camera FinePix
J27/J28/J29/J30/J32/J37/J38 Owner-s Manual, pp99-104.
[36] Canon Inc., Canon EOS 50D Instruction Manual, pp204-210, 2008
[1] O. T. Tsuchiya., Measure Against Lifestyle Related Disease, JMAJ,
Vol.49 no.3, 2006, pp132-134.
[2] E. Duh, Diabetic Retinopathy, Humana Press, 2008, pp29-66
[3] American Diabetes Association, Diabetic retinopathy, Clinical Diabetes,
Vol. 19, No. 1, 2001, pp29-32
[4] S. S. Savant and H. B. Chandalia, Diabetic retinopathy, Intnl. J. Dev.
Contries, Vol. 10, 1991, pp,9-25
[5] J. B. Brown, K. L. Pedula, K. H. Summers, Diabetic retinopathy,
Diabetes Care, Vol. 26, No. 9, 2003, pp2637-2642.
[6] S. Garg and R. M. Davis, Diabetic retinopathy screening update, Clinical
diabetes, Vo. 27, No. 4, 2009, pp140-145.
[7] I. U. Scott, N. M. Bressler, S. B. Bresseler et al, Agreement between
clinical and reading center gradings of diabetic retinopathy severity level
at baseline in a phase 2 study of intravitreal bevacizumab for diabetic
macular edema, Retina, Vol. 28, No. 1, 2008, pp36-40.
[8] M. S. Figueroa, I . Contreras, S. Noval, Anti-angiogetic drugs as an
adjunctive therapy in the surgical treatment of diabetic retinopathy, Curr
Diabetes Rev., Vol. 5, No. 1, 2009, pp52-56.
[9] A.G. Oomen, J. P. C. M. Janssen, A. Dusseldorp et al., Ecposure to
chemicals via house dust, RIVM Report 609021064/2008, 2008,
pp11-18.
[10] E. Fernández-Caldas, W. L. Trudeau and D. K. Ledford, Environmental
control of indoor biologic agents. J. Allergy. Clin. Immunol., issue 2, part
2, 1994, pp404-412.
[11] R. G. Willson, M. W. Maimone, A. E. Johnson et al, An Optical Model for
Image Artifacts Produced by Dust Particles on Lenses, Proc. ISAIRAS
2005 Conference, 2005, ESA SP p603.
[12] A.V. Shukla, Clinical Optics Primer for Ophthalmic Medical Personnel,
A Guide to Laws, Formulae, Calculations, and Clinical Applications,
SLACK Inc. 2009, pp85-89.
[13] M. Born and E. Wolf, Principles of Optics 7th expanded edition,
Electromagnetic Theory of Propagation, Interference and Diffraction of
Light, Cambridge Univ. Press, 1999, pp142-227.
[14] D. D. David, R. Prescott, and S. Kennedy, Simultaneous stereoscopic
fundus camera incorporating a single optical axis, Invest. Ophthalmol.
Vis. Sci. March, 1980, pp289-297.
[15] R. Zeimer, S. Zou, T. Meeder et al, A fundus camera dedicated to the
screening of diabetic retinopathy in the primary-care physician-s office,
IOVS May, Vol. 43, No. 5, 2002, pp1581-1587
[16] M. Niemeijer, B. Ginneken, S. R. Russell et al, Automated detection and
differential of drusen, exudates, and cotton-wool spots in digital color
fundus photographs for diabetic retinopathy diagnosis, Invest.
Ophthalmol. Vis. Sci., Vol. 48, No. 5, 2007, pp2260-2267.
[17] D.Y. Lin, M. S. Blumenkrans, R. J. Brothers et al, The sensitivity and
specificity of single-field nonmydriatic monochromatic digital fundus
photography with remote image interpretation for diabetic retinopathy
screening: a comparison with ophthalmoscopy and standardized
mydriatic color photography, Am. J. Ophthalmol., Vol. 134, 2002,
pp204-213.
[18] J. A. Olson, F. M. Strachan, J. H. Hipwell et al, A comparative evaluation
of digital imaging, retinal photography and optometrist examination in
screening for diabetic retinopathy, Diabet. Med., Vol. 20, 2003,
pp528-534.
[19] A. E. Dirik, H. T. Sencar and N. Memon, Source Camera Identification
Based on Sensor dust Characteristics, Signal Processing Applications for
Public Security and Forensics 2007, SAFE-07, IEEE Workshop, 2007,
pp1-6.
[20] R. Bergman, R. Maurer, H. Nachlieli et al, Comprehensive Solutions for
Removal of Dust and Scratches from Images, Journal of Electronic
Imaging, Vol. 17, No. 1, 2008, pp1-25.
[21] A. Zamfir, A. Drimbarean, M. Zamfir et al., An Optic Model of the
Appearance of Blemishes in Digital Photographs, Proceedings of SPIE,
Vol. 6502, Digital Photography 3, 2007.
[22] A. E. Dirik, H. T. Sencar and N. Memon, Digital Single Lens Reflex
Camera Identification From Traces of Sensor Dust, IEEE Trans. Info. For.
and Sec., Vol. 3, No. 3, 2008, pp539-552.
[23] R. F. Lyon, Prism-Based Color Separation for Professional Digital
Photography, Proceedings of IS&T-s PICS 2000 Conference: Image
Processing, Image Quality, Image Capture Systems Conference, Oregon,
2000, pp50-54.
[24] H. Narasimha-Iyer, A. Can, B. Roysam et al., Robust Detection and
Classification of Longitudinal Changes in Color Retinal Fundus Images
for Monitoring Diabetic Retinopathy, IEEE Trans. Biomed. Eng., Vol.
53, No. 6, 2006, pp1084-1098.
[25] H. Narasima-lyer, A. Can, B. Roysam et al, Integrated analysis of vascular
and nonvascular changes from color retinal fundus image sequences.,
IEEE Trans Biomed Eng., Vol. 54, No. 8, 2007, pp1436-45.
[26] P. J. Saine, Errors in Fundus Photography, Journal of Ophthalmic
Photography, Vol. 7, No. 2, 1984, pp120-122.
[27] M. Tkalˇciˇc & F. J. Tasiˇc, Colour spaces - perceptual , historical and
applicational background, EUROCON 2003, Computer as a tool, The
IEEE Region 8, Vol.1, 2003, pp304-308.
[28] J. Koenderink, Colour for the sciences, The MIT Press, 2009, pp45-52,
pp497-537.
[29] B. Jahne, Practical Handbook on Image Processing for Scientific
Applications, CRC Press, 1997, pp102-107.
[30] B. G. Haskell, A. Puri and A. N. Netravali, Digital Video: An Introduction
to MPEG-2, Chapman & Hall, 1997, pp86-91.
[31] A. Hanbury and J. Serra, Mathematical Morphology in the HLS Colour
Space, 12th British Machine Vision Conference, Manchester, UK, 2001,
pp 451-460.
[32] Jasc Software, Inc., Chapter 8: Making color and Tonal Corrections, Paint
Shop Pro 8 User Guide, 2002, pp181-206.
[33] R. A. Peters II, Mathematical morphology for angle-valued images,
Proceedings of the SPIE, Nonlinear Image Processing VIII 3026, 1997,
pp84-94.
[34] Nikon Corporations, Nikon D1X Operators Manual, pp212-219.
[35] FUJIFILM Corporation, Digital Camera FinePix
J27/J28/J29/J30/J32/J37/J38 Owner-s Manual, pp99-104.
[36] Canon Inc., Canon EOS 50D Instruction Manual, pp204-210, 2008
@article{"International Journal of Medical, Medicine and Health Sciences:58242", author = "Naoto Suzuki", title = "Basic Research for Distinguishing Small Retinal Hemorrhages from Dust Artifact by using Hue, Lightness, and Saturation Color Space", abstract = "To distinguish small retinal hemorrhages in early
diabetic retinopathy from dust artifacts, we analyzed hue, lightness,
and saturation (HLS) color spaces. The fundus of 5 patients with
diabetic retinopathy was photographed. For the initial experiment, we
placed 4 different colored papers on the ceiling of a darkroom. Using
each color, 10 fragments of house dust particles on a magnifier were
photographed. The colored papers were removed, and 3 different
colored light bulbs were suspended from the ceiling. Ten fragments of
house dust particles on the camera-s object lens were photographed.
We then constructed an experimental device that can photograph
artificial eyes. Five fragments of house dust particles under the ocher
fundus of the artificial eye were photographed. On analyzing HLS
color space of the dust artifact, lightness and saturation were found to
be highly sensitive. However, hue was not highly sensitive.", keywords = "Dust artifact, HLS color space, Retinal hemorrhage,and Diabetic retinopathy", volume = "6", number = "5", pages = "154-9", }
