Prof. Madhusudhanan Balasubramanian Profile

Prof. Madhusudhanan Balasubramanian

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Publications (5)

SPIE Journal Paper | 29 December 2014

Glaucoma progression detection using nonlocal Markov random field prior

Akram Belghith, Christopher Bowd, Felipe Medeiros, Madhusudhanan Balasubramanian, Robert Weinreb, Linda Zangwill

JMI, Vol. 1, Issue 03, 034504, (December 2014) https://doi.org/10.1117/12.10.1117/1.JMI.1.3.034504

KEYWORDS: 3D image processing, Optical coherence tomography, Computer simulations, Visualization, Optic nerve, Diagnostics, Fuzzy logic, Eye, 3D modeling, Fusion energy

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SPIE Journal Paper | 1 July 2007

Real-time restoration of white-light confocal microscope optical sections

Madhusudhanan Balasubramanian, S. Sitharama Iyengar, Roger Beuerman, Juan Reynaud, Peter Wolenski

JEI, Vol. 16, Issue 03, 033009, (July 2007) https://doi.org/10.1117/12.10.1117/1.2768092

KEYWORDS: Confocal microscopy, Digital filtering, Image filtering, Deconvolution, Point spread functions, Image processing, Lawrencium, Microscopes, Image restoration, Optical fibers

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Proceedings Article | 29 March 2007 Paper

Retinal oxygen saturation evaluation by multi-spectral fundus imaging

Bahram Khoobehi, Jinfeng Ning, Elise Puissegur, Kimberly Bordeaux, Madhusudhanan Balasubramanian, James Beach

Proceedings Volume 6511, 65110B (2007) https://doi.org/10.1117/12.710030

KEYWORDS: Oxygen, Retina, Arteries, Tissues, Veins, Cameras, Eye, Image registration, Blood, Reflectivity

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Purpose: To develop a multi-spectral method to measure oxygen saturation of the retina in the human eye. Methods: Five Cynomolgus monkeys with normal eyes were anesthetized with intramuscular ketamine/xylazine and intravenous pentobarbital. Multi-spectral fundus imaging was performed in five monkeys with a commercial fundus camera equipped with a liquid crystal tuned filter in the illumination light path and a 16-bit digital camera. Recording parameters were controlled with software written specifically for the application. Seven images at successively longer oxygen-sensing wavelengths were recorded within 4 seconds. Individual images for each wavelength were captured in less than 100 msec of flash illumination. Slightly misaligned images of separate wavelengths due to slight eye motion were registered and corrected by translational and rotational image registration prior to analysis. Numerical values of relative oxygen saturation of retinal arteries and veins and the underlying tissue in between the artery/vein pairs were evaluated by an algorithm previously described, but which is now corrected for blood volume from averaged pixels (n > 1000). Color saturation maps were constructed by applying the algorithm at each image pixel using a Matlab script. Results: Both the numerical values of relative oxygen saturation and the saturation maps correspond to the physiological condition, that is, in a normal retina, the artery is more saturated than the tissue and the tissue is more saturated than the vein. With the multi-spectral fundus camera and proper registration of the multi-wavelength images, we were able to determine oxygen saturation in the primate retinal structures on a tolerable time scale which is applicable to human subjects. Conclusions: Seven wavelength multi-spectral imagery can be used to measure oxygen saturation in retinal artery, vein, and tissue (microcirculation). This technique is safe and can be used to monitor oxygen uptake in humans. This work is original and is not under consideration for publication elsewhere.

Proceedings Article | 24 August 2006 Paper

Fractal dimension based corneal fungal infection diagnosis

Madhusudhanan Balasubramanian, A. Louise Perkins, Roger Beuerman, S. Sitharama Iyengar

Proceedings Volume 6312, 631214 (2006) https://doi.org/10.1117/12.680041

KEYWORDS: Fractal analysis, Confocal microscopy, Fungi, Cornea, Microscopes, Image filtering, Feature extraction, Eye, Image classification, Binary data

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Proceedings Article | 16 September 2005 Paper

Adaptive noise filtering of white-light confocal microscope images using Karhunen-Loève expansion

M. Balasubramanian, S. S. Iyengar, P. Wolenski, J. Reynaud, R. Beuerman

Proceedings Volume 5909, 590904 (2005) https://doi.org/10.1117/12.615252

KEYWORDS: Digital filtering, Image filtering, Confocal microscopy, Electronic filtering, Microscopes, Optical filters, Deconvolution, Vector spaces, Point spread functions, Image restoration

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