Bartlomiej Kowalski
Software Dvlpr 3, Ophthalmology Research/Clinical Trials
Bio
I am a senior software engineer in the Dubra Lab at The Byers Eye Institute, where I work on developing novel ophthalmic imaging instrumentation for improving the understanding, diagnosing and management of eye disease.
My interest in computer science started early in life and led me to obtain master’s degree at Czestochowa University of Technology (Poland). After graduating, I contributed to the advancing of spectral domain optical coherence tomography (OCT) and pioneering of swept-source OCT for retinal imaging as part of Canon Ophthalmic Technologies (Poland). This work resulted in two commercially successful instruments, the Xephilio OCT-A1 and the Xephilio OCT-S1, which are sold worldwide.
My current work focuses on innovations that allow the translation of Adaptive Optics Ophthalmoscopy from a research tool into a mature technology that improves eye care.
Education & Certifications
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Master degree, Czestochowa University of Technology (Poland), Computer science (2010)
All Publications
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Normalized weighted cross correlation for multi-channel image registration
OPTICS CONTINUUM
2024; 3 (5): 649-665
View details for DOI 10.1364/OPTCON.525065
View details for Web of Science ID 001214608900003
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Sub-diffraction adaptive optics fluorescence imaging of the living human eye using pixel reassignment
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2023
View details for Web of Science ID 001053758305234
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Longitudinal imaging of microscopic scattering features in the foveal avascular zone of multiple sclerosis using adaptive optics ophthalmoscopy
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2023
View details for Web of Science ID 001053795604033
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Surpassing the diffraction limit for improved resolution in adaptive optics optical coherence tomography in the living human eye
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2023
View details for Web of Science ID 001053758302333
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Correction of non-uniform angular velocity and sub-pixel jitter in optical scanning
Optics Express
2022; 30 (1): 112-124
View details for DOI 10.1364/OE.446162
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Hybrid FPGA-CPU pupil tracker.
Biomedical optics express
2021; 12 (10): 6496-6513
Abstract
An off-axis monocular pupil tracker designed for eventual integration in ophthalmoscopes for eye movement stabilization is described and demonstrated. The instrument consists of light-emitting diodes, a camera, a field-programmable gate array (FPGA) and a central processing unit (CPU). The raw camera image undergoes background subtraction, field-flattening, 1-dimensional low-pass filtering, thresholding and robust pupil edge detection on an FPGA pixel stream, followed by least-squares fitting of the pupil edge pixel coordinates to an ellipse in the CPU. Experimental data suggest that the proposed algorithms require raw images with a minimum of ∼32 gray levels to achieve sub-pixel pupil center accuracy. Tests with two different cameras operating at 575, 1250 and 5400 frames per second trained on a model pupil achieved 0.5-1.5 μm pupil center estimation precision with 0.6-2.1 ms combined image download, FPGA and CPU processing latency. Pupil tracking data from a fixating human subject show that the tracker operation only requires the adjustment of a single parameter, namely an image intensity threshold. The latency of the proposed pupil tracker is limited by camera download time (latency) and sensitivity (precision).
View details for DOI 10.1364/BOE.433766
View details for PubMedID 34745752
View details for PubMedCentralID PMC8548015
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Dynamic wavefront distortion in resonant scanners
Applied Optics
2021; 60 (36): 11189-11195
View details for DOI 10.1364/AO.443972
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Novel microscopic foveal pit pathology in multiple sclerosis revealed with adaptive optics ophthalmoscopy
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2020
View details for Web of Science ID 000554528304317
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Dynamic distortion in resonant galvanometric optical scanners
Optica
2020; 7 (11)
View details for DOI 10.1364/OPTICA.405187
- Wavefront distortions in an oscillating resonant galvanometric optical scanner Computational Optical Sensing and Imaging 2020: JW2A. 48
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Non-confocal quad-detection adaptive optics scanning light ophthalmoscopy of the photoreceptor mosaic
ASSOC RESEARCH VISION OPHTHALMOLOGY INC. 2018
View details for Web of Science ID 000442932804115