Dr. Isaac Y. August Profile

Dr. Isaac Y. August

SPIE Involvement:

Author

Area of Expertise:

Spectral imaging , Compressive sensing , Nural networks , Computational optics , Image processing

Publications (13)

SPIE Journal Paper | 9 September 2023 Open Access

Compressive hyperspectral microscopy for cancer detection

Yaniv Oiknine, Marwan Abuleil, Eugene Brozgol, Isaac August, Iris Barshack, Ibrahim Abdulhalim, Yuval Garini, Adrian Stern

JBO, Vol. 28, Issue 09, 096502, (September 2023) https://doi.org/10.1117/12.10.1117/1.JBO.28.9.096502

KEYWORDS: Microscopes, Microscopy, Light sources and illumination, Cancer detection, Imaging spectroscopy, Imaging systems, Biopsy, Optical filters, Tunable filters, Medical image reconstruction

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SignificanceHyperspectral microscopy grants the ability to characterize unique properties of tissues based on their spectral fingerprint. The ability to label and measure multiple molecular probes simultaneously provides pathologists and oncologists with a powerful tool to enhance accurate diagnostic and prognostic decisions. As the pathological workload grows, having an objective tool that provides companion diagnostics is of immense importance. Therefore, fast whole-slide spectral imaging systems are of immense importance for automated cancer prognostics that meet current and future needs.AimWe aim to develop a fast and accurate hyperspectral microscopy system that can be easily integrated with existing microscopes and provide flexibility for optimizing measurement time versus spectral resolution.ApproachThe method employs compressive sensing (CS) and a spectrally encoded illumination device integrated into the illumination path of a standard microscope. The spectral encoding is obtained using a compact liquid crystal cell that is operated in a fast mode. It provides time-efficient measurements of the spectral information, is modular and versatile, and can also be used for other applications that require rapid acquisition of hyperspectral images.ResultsWe demonstrated the acquisition of breast cancer biopsies hyperspectral data of the whole camera area within ∼1 s. This means that a typical 1 × 1 cm2 biopsy can be measured in ∼10 min. The hyperspectral images with 250 spectral bands are reconstructed from 47 spectrally encoded images in the spectral range of 450 to 700 nm.ConclusionsCS hyperspectral microscopy was successfully demonstrated on a common lab microscope for measuring biopsies stained with the most common stains, such as hematoxylin and eosin. The high spectral resolution demonstrated here in a rather short time indicates the ability to use it further for coping with the highly demanding needs of pathological diagnostics, both for cancer diagnostics and prognostics.

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Proceedings Article | 16 May 2018 Presentation + Paper

3D reconstructions from spectral light fields

Vladimir Farber, Yaniv Oiknine, Isaac August, Adrian Stern

Proceedings Volume 10666, 106660W (2018) https://doi.org/10.1117/12.2306139

KEYWORDS: Imaging systems, Integral imaging, Hyperspectral imaging

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SPIE Journal Paper | 5 March 2018

Spectral light fields for improved three-dimensional profilometry

Vladimir Farber, Yaniv Oiknine, Isaac August, Adrian Stern

OE, Vol. 57, Issue 06, 061609, (March 2018) https://doi.org/10.1117/12.10.1117/1.OE.57.6.061609

KEYWORDS: Cameras, Imaging systems, Integral imaging, Reconstruction algorithms, Two photon polymerization, Optical engineering, Imaging arrays, Hyperspectral imaging, 3D image processing, Light

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Proceedings Article | 4 October 2017 Paper

Target detection with compressive sensing hyperspectral images

Yaniv Oiknine, Daniel Gedalin, Isaac August, Dan Blumberg, Stanley Rotman, Adrian Stern

Proceedings Volume 10427, 104270O (2017) https://doi.org/10.1117/12.2277186

KEYWORDS: Target detection, Detection and tracking algorithms, Compressed sensing, Liquid crystals, Imaging systems, Signal detection, Hyperspectral imaging, Multiplexing, Compressive imaging, Spectral imaging cameras, Hyperspectral target detection

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Proceedings Article | 6 September 2017 Presentation + Paper

Method and algorithm for efficient calibration of compressive hyperspectral imaging system based on a liquid crystal retarder

Liat Shecter, Yaniv Oiknine, Isaac August, Adrian Stern

Proceedings Volume 10410, 104100C (2017) https://doi.org/10.1117/12.2278186

KEYWORDS: Liquid crystals, Calibration, Sensors, Modulators, Hyperspectral imaging, Imaging systems, Wave plates, Compressed sensing, Sensor calibration, Reconstruction algorithms

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Proceedings Article | 16 May 2017 Paper

Compressive spectroscopy by spectral modulation

Yaniv Oiknine, Isaac August, Adrian Stern

Proceedings Volume 10231, 102310K (2017) https://doi.org/10.1117/12.2261403

KEYWORDS: Modulation, Liquid crystals, Spectroscopy, Compressed sensing, Fabry–Perot interferometers, Resonators, Wave plates, Hyperspectral imaging, Image compression, Imaging systems, Mirrors, Light emitting diodes, Green light emitting diodes, Multiplexing, Compressive imaging, Hyperspectral sensing, Optical multiplexing

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SPIE Journal Paper | 9 January 2017

Performance of target detection algorithm in compressive sensing miniature ultraspectral imaging compressed sensing system

Daniel Gedalin, Yaniv Oiknine, Isaac August, Dan Blumberg, Stanley Rotman, Adrian Stern

OE, Vol. 56, Issue 04, 041312, (January 2017) https://doi.org/10.1117/12.10.1117/1.OE.56.4.041312

KEYWORDS: Detection and tracking algorithms, Target detection, Compressed sensing, Multiplexing, Imaging systems, Sensing systems, Reconstruction algorithms, Miniature imaging systems, Liquid crystals, Computing systems

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Proceedings Article | 2 November 2016 Presentation

Stokes polarimetry, narrowband filtering, and hyperspectral imaging using a small number of liquid crystal devices (Conference Presentation)

Marwan Abuleil, Isaac August, Yaniv Oiknine, Adrian Stern, Ibrahim Abdulhalim

Proceedings Volume 9940, 99400S (2016) https://doi.org/10.1117/12.2237295

KEYWORDS: Liquid crystals, Tunable filters, Imaging systems, Polarimetry, Hyperspectral imaging, LCDs, Polarization, Wave plates, Tissue optics, Image filtering

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Proceedings Article | 20 May 2016 Paper

Hurdles in the implementation of compressive sensing for imaging and ways to overcome them

Adrian Stern, Isaac August, Yaniv Oiknine

Proceedings Volume 9870, 987006 (2016) https://doi.org/10.1117/12.2224702

KEYWORDS: Compressive imaging, Compressed sensing, Imaging systems, Holography, Optical imaging, Imaging spectroscopy, Image compression, Radon, Sensors, Liquid crystals

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Proceedings Article | 4 May 2016 Paper

Comparison between various patch wise strategies for reconstruction of ultra-spectral cubes captured with a compressive sensing system

Yaniv Oiknine, Isaac August, Liat Revah, Adrian Stern

Proceedings Volume 9857, 985705 (2016) https://doi.org/10.1117/12.2223647

KEYWORDS: Compressed sensing, Sensing systems, Data processing, Liquid crystals, Sensors, Wavelets, Miniature imaging systems, Imaging systems, Reconstruction algorithms, Wave plates

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Proceedings Article | 14 May 2015 Paper

Compressive and classical hyperspectral systems: a fundamental comparison

Adi Shay, Isaac August, Adrian Stern

Proceedings Volume 9484, 948408 (2015) https://doi.org/10.1117/12.2177587

KEYWORDS: Imaging systems, Hyperspectral imaging, Image compression, Remote sensing, Compressed sensing, Imaging spectroscopy, Spectroscopy, Optical filters, Optical components, Hyperspectral systems

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Proceedings Article | 23 September 2014 Paper

Reconstruction algorithms for compressive hyperspectral imaging systems with separable spatial and spectral operators

Yaniv Oiknine, Yitzhak August, Adrian Stern

Proceedings Volume 9217, 921703 (2014) https://doi.org/10.1117/12.2064640

KEYWORDS: Reconstruction algorithms, Imaging systems, Hyperspectral imaging, Compressed sensing, Sensing systems, Multiplexing, MATLAB, Computer programming, Optimization (mathematics), Computer simulations

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Proceedings Article | 31 May 2013 Paper

Spatial versus spectral compression ratio in compressive sensing of hyperspectral imaging

Yitzhak August, Chaim Vachman, Adrian Stern

Proceedings Volume 8717, 87170G (2013) https://doi.org/10.1117/12.2017949

KEYWORDS: Hyperspectral imaging, Image compression, Cameras, Compressed sensing, Principal component analysis, Imaging systems, Image quality, Matrices, Multiplexing, Signal processing

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Showing 5 of 13 publications

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