Shape-based multi-spectral optical image reconstruction through genetic algorithm based optimization

Wang, Song; Dhawan, Atam P.

doi:10.1016/j.compmedimag.2008.04.006

Cited by 11 publications

(8 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Changes in local hemodynamic response have been recorded through transillumination imaging, diffuse reflectance tomography and photoacoustic imaging with clinical applications to brain imaging and detection of breast and skin cancers [155], [157], [262], [263]. A series of dynamic 2-D images have been obtained to delineate the time course of concentration changes of oxyhemoglobin, deoxyhemoglobin, and total hemoglobin in the rat brain during seizure onset [224], [261].…”

Section: Discussion and Concluding Remarksmentioning

confidence: 99%

“…The difference between these measurements is then fed into the reconstruction algorithm to obtain the optical properties. Since this is an extremely ill-posed inverse solution problem, a priori shape information can be used to find a reasonable solution as shown by several investigators [23], [157]- [160]. A generalized lesion reconstruction method from multispectral diffuse reflectance using shape based information is schematically shown in Fig.…”

Section: O Diffuse Reflectance and Transillumination Imagingmentioning

confidence: 98%

“…The simulated multispectral transillumination images acquired with the Nevoscope were fed into a genetic algorithm-based optimization program where the optical properties were reconstructed in terms of measurements at multiple wavelengths. The distribution of melanin and blood was subsequently calculated by Wang and Dhawan [157]. Results of the reconstruction of melanin and blood parts were presented for simulated lesions using multispectral wavelengths at 580 nm and 800 nm.…”

Section: O Diffuse Reflectance and Transillumination Imagingmentioning

confidence: 99%

See 2 more Smart Citations

Optical Imaging Modalities for Biomedical Applications

Dhawan

D'Alessandro

2010

IEEE Rev. Biomed. Eng.

Self Cite

View full text Add to dashboard Cite

Optical photographic imaging is a well known imaging method that has been successfully translated into biomedical applications such as microscopy and endoscopy. Although several advanced medical imaging modalities are used today to acquire anatomical, physiological, metabolic, and functional information from the human body, optical imaging modalities including optical coherence tomography, confocal microscopy, multiphoton microscopy, multispectral endoscopy, and diffuse reflectance imaging have recently emerged with significant potential for non-invasive, portable, and cost-effective imaging for biomedical applications spanning tissue, cellular, and molecular levels. This paper reviews methods for modeling the propagation of light photons in a biological medium, as well as optical imaging from organ to cellular levels using visible and near-infrared wavelengths for biomedical and clinical applications.

show abstract

Section: Discussion and Concluding Remarksmentioning

confidence: 99%

Section: O Diffuse Reflectance and Transillumination Imagingmentioning

confidence: 98%

Section: O Diffuse Reflectance and Transillumination Imagingmentioning

confidence: 99%

See 1 more Smart Citation

Optical Imaging Modalities for Biomedical Applications

Dhawan

D'Alessandro

2010

IEEE Rev. Biomed. Eng.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Hence using single harmonic response results in an under-determined problem. Genetic optimization technique has been applied to under-determined problems to obtain approximate solutions with satisfactory accuracy (Wang and Dhawan, 2008). Here genetic algorithm has been improved by combining sub-space and zooming techniques.…”

Section: Set-up Of the Genetic Algorithmmentioning

confidence: 99%

Modeling of Biological Interfacial Processes Using Thickness–Shear Mode Sensors

Ergezen¹,

Desa²,

Hochman³

et al. 2011

Acoustic Waves - From Microdevices to Helioseismology

View full text Add to dashboard Cite

“…Since no general-purpose optimization algorithm exists that has the best performance in all classes of problems [19], the advantage of a genetic algorithm over other heuristic algorithms can be demonstrated in specifi c types of problems. In optics and spectroscopy, genetic algorithms have been successfully applied for analysis and processing of spectra [20], approximation of the phase shift in interferograms [21], retrieval of multispectral images [22], and spectral calibration [23].…”

mentioning

confidence: 99%

Retrieval of Spectra from Interferograms with a Small Optical Path Difference Using a Genetic Algorithm

Gulis

Kupreyeu

2015

J Appl Spectrosc

View full text Add to dashboard Cite

We propose a method for retrieval of an optical line spectrum limited to a narrow spectral range using a short interferogram, based on the use of a multi-stage genetic algorithm. We have run simulations for the example of spectra with lines having wavenumbers lying in the 100 cm -1 range, and the maximum optical path difference for the interferograms was 1200 μm. We show that the spectral resolution can be improved by a factor of 3-4 compared with Fourier transform estimation.Introduction. Interference spectral instruments have high luminosity, low signal-to-noise ratio as a result of multiplexing, and a broad working spectral range. Retrieval of the spectrum in conventional Fourier transform spectroscopy is based on the Wiener-Khinchin theorem, relating the power spectral density for a stationary random process to its autocorrelation function (interference pattern or interferogram) by means of a Fourier transform [1]. In this case, the theoretical spectral resolution is inversely proportional to the maximum optical path difference, and therefore it is low in compact instruments.It is diffi cult to substantially improve the resolution of compact instruments strictly with hardware. Fast continuous scanning, used in popular laboratory Fourier transform spectrometers, requires a high-precision drive and constant operating parameters of the instrument for high-quality retrieval of the spectrum, which is complicated to achieve in a small instrument [2]. Experimental systems using scanning of the optical path difference in a more compact size (for example, using a Wollaston prism [3] or in a standing-wave interferometer [4]) do not provide a substantial increase (by a factor of 3-5) in the spectral resolution and generally form a poorer quality interferogram. Recording a stationary interferogram based on a multi-element photodetector makes it possible to dispense with the scanning mechanism and thus to reduce the size of the instrument [5-7]. However, due to the small number of pixels in the detector, an increase in the length of the interferogram causes narrowing of the spectral range for retrieval. Parallel recording of sections of the interferogram on a two-dimensional photodetector and "splicing" them into one interferogram with a large effective length requires, in addition to complicated post-processing, an increase in the dimensions of the optical part of the instrument while maintaining light beam homogeneity [8]. Recording the interferograms from different spectral intervals on different regions of the same two-dimensional array decreases the infl uence of noise at individual frequencies on the rest of the spectrum, but the spectral resolution for each of the intervals remains poor since the interferogram is short [9].Alternatives to the Fourier transform method for spectral estimation in some cases (more often for quasi-line spectra) let us improve the spectral resolution without increasing the maximum path difference. For example, knowing the mathematical model for the signal a priori in autoregression metho...

show abstract

Shape-based multi-spectral optical image reconstruction through genetic algorithm based optimization

Cited by 11 publications

References 31 publications

Optical Imaging Modalities for Biomedical Applications

Optical Imaging Modalities for Biomedical Applications

Modeling of Biological Interfacial Processes Using Thickness–Shear Mode Sensors

Retrieval of Spectra from Interferograms with a Small Optical Path Difference Using a Genetic Algorithm

Contact Info

Product

Resources

About