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Removal of subsurface fluorescence in cryo-imaging using deconvolution.

ABSTRACT: We compared image restoration methods [Richardson-Lucy (RL), Wiener, and Next-image] with measured "scatter" point-spread-functions, for removing subsurface fluorescence from section-and-image cryo-image volumes. All methods removed haze, delineated single cells from clusters, and improved visualization, but RL best represented structures. Contrast-to-noise and contrast-to-background improvement from RL and Wiener were comparable and 35% better than Next-image. Concerning detection of labeled cells, ROC analyses showed RL ?Wiener > Next-image >> no processing. Next-image was faster than other methods and less prone to image processing artifacts. RL is recommended for the best restoration of the shape and size of fluorescent structures.

SUBMITTER: Krishnamurthi G

PROVIDER: S-EPMC3408948 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature

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Removal of subsurface fluorescence in cryo-imaging using deconvolution.

Krishnamurthi Ganapathy G Wang Charlie Y CY Steyer Grant G Wilson David L DL

Optics express 20101001 21

We compared image restoration methods [Richardson-Lucy (RL), Wiener, and Next-image] with measured "scatter" point-spread-functions, for removing subsurface fluorescence from section-and-image cryo-image volumes. All methods removed haze, delineated single cells from clusters, and improved visualization, but RL best represented structures. Contrast-to-noise and contrast-to-background improvement from RL and Wiener were comparable and 35% better than Next-image. Concerning detection of labeled ce ...[more]

PMID: 20941133

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Project description:SignificanceFluorescence guidance is used clinically by surgeons to visualize anatomical and/or physiological phenomena in the surgical field that are difficult or impossible to detect by the naked eye. Such phenomena include tissue perfusion or molecular phenotypic information about the disease being resected. Conventional fluorescence-guided surgery relies on long, microsecond scale laser pulses to excite fluorescent probes. However, this technique only provides two-dimensional information; crucial depth information, such as the location of malignancy below the tissue surface, is not provided.AimWe developed a depth sensing imaging technique using light detection and ranging (LiDAR) time-of-flight (TOF) technology to sense the depth of target tissue while overcoming the influence of tissue optical properties and fluorescent probe concentration.ApproachThe technology is based on a large-format (512×512 pixel), binary, gated, single-photon avalanche diode (SPAD) sensor with an 18 ps time-gate step, synchronized with a picosecond pulsed laser. The fast response of the sensor was developed and tested for its ability to quantify fluorescent inclusions at depth and optical properties in tissue-like phantoms through analytical model fitting of the fast temporal remission data.ResultsAfter calibration and algorithmic extraction of the data, the SPAD LiDAR technique allowed for sub-mm resolution depth sensing of fluorescent inclusions embedded in tissue-like phantoms, up to a maximum of 5 mm in depth. The approach provides robust depth sensing even in the presence of variable tissue optical properties and separates the effects of fluorescence depth from absorption and scattering variations.ConclusionsLiDAR TOF fluorescence imaging using an SPAD camera provides both fluorescence intensity images and the temporal profile of fluorescence, which can be used to determine the depth at which the signal is emitted over a wide field of view. The proposed tool enables fluorescence imaging at a higher depth in tissue and with higher spatial precision than standard, steady-state fluorescence imaging tools, such as intensity-based near-infrared fluorescence imaging, optical coherence tomography, Raman spectroscopy, or confocal microscopy. Integration of this technique into a standard surgical tool could enable rapid, more accurate estimation of resection boundaries, thereby improving the surgeon's efficacy and efficiency, and ultimately improving patient outcomes.

Dataset Information

Removal of subsurface fluorescence in cryo-imaging using deconvolution.

Publications

Removal of subsurface fluorescence in cryo-imaging using deconvolution.

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