A review of snapshot multidimensional optical imaging: Measuring photon tags in parallel

Gao, Liang; Wang, Lihong V.

doi:10.1016/j.physrep.2015.12.004

Cited by 128 publications

(50 citation statements)

References 232 publications

(312 reference statements)

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“…Hence, its application is restricted in fields such as ultra-fast imaging [60,61]. Recently, remarkable snap-shot spectral imaging techniques have been widely developed to acquire a 3D spectral data-cube in just a single exposure [62][63][64][65][66]. However, since the correlation between pixels and wavelengths of the 3D image data-cube is not utilized in these methods, the information acquisition efficiency is lower than the Shannon limit [67,68].…”

Section: Gisc Spectral Cameramentioning

confidence: 99%

A Review of Ghost Imaging via Sparsity Constraints

Han

Shen

et al. 2018

Applied Sciences

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Different from conventional imaging methods, which are based on the first-order field correlation, ghost imaging (GI) obtains the image information through high-order mutual-correlation of light fields from two paths with an object appearing in only one path. As a new optical imaging technology, GI not only provides us new capabilities beyond the conventional imaging methods, but also gives out a new viewpoint of imaging physical mechanism. It may be applied to many potential applications, such as remote sensing, snap-shot spectral imaging, thermal X-ray diffraction imaging and imaging through scattering media. In this paper, we reviewed mainly our research work of ghost imaging via sparsity constraints (GISC) and discussed the application and theory prospect of GISC concisely.

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Section: Gisc Spectral Cameramentioning

confidence: 99%

A Review of Ghost Imaging via Sparsity Constraints

Han

Shen

et al. 2018

Applied Sciences

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“…Even with the latest advancements in imaging technology, incomplete tumor resection in patients with breast cancer is at an alarming rate of 20 to 25 percent, with recurrence rates of up to 27 percent [2]. The clinical need for imaging instruments that provide real-time feedback in the operating room is unmet, largely due to the use of imaging systems based on contemporary technological advances in the semiconductor and optical fields, which have bulky and costly designs with suboptimal sensitivity and co-registration accuracy between multimodal images [3–7]. …”

Section: Introductionmentioning

confidence: 99%

Bio-inspired imager improves sensitivity in near-infrared fluorescence image-guided surgery

Garcia

Edmiston

York

et al. 2018

Optica

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Image-guided surgery can enhance cancer treatment by decreasing, and ideally eliminating, positive tumor margins and iatrogenic damage to healthy tissue. Current state-of-the-art near-infrared fluorescence imaging systems are bulky and costly, lack sensitivity under surgical illumination, and lack co-registration accuracy between multimodal images. As a result, an overwhelming majority of physicians still rely on their unaided eyes and palpation as the primary sensing modalities for distinguishing cancerous from healthy tissue. Here we introduce an innovative design, comprising an artificial multispectral sensor inspired by the Morpho butterfly’s compound eye, which can significantly improve image-guided surgery. By monolithically integrating spectral tapetal filters with photodetectors, we have realized a single-chip multispectral imager with 1000 × higher sensitivity and 7 × better spatial co-registration accuracy compared to clinical imaging systems in current use. Preclinical and clinical data demonstrate that this technology seamlessly integrates into the surgical workflow while providing surgeons with real-time information on the location of cancerous tissue and sentinel lymph nodes. Due to its low manufacturing cost, our bio-inspired sensor will provide resource-limited hospitals with much-needed technology to enable more accurate value-based health care.

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“…These measured intensities over all spatial and spectral points constitute a three-dimensional ( x, y, λ ) datacube. 1–4 Typically, when collecting this datacube, hyperspectral imaging requires either spatial scanning or spectral filtering. However, in recent years, various snapshot hyperspectral imaging techniques have been developed to obtain the three-dimensional ( x, y, λ ) information within a single exposure.…”

Section: Introductionmentioning

confidence: 99%

High spatial sampling light-guide snapshot spectrometer

2017

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A prototype fiber-based imaging spectrometer was developed to provide snapshot hyperspectral imaging tuned for biomedical applications. The system is designed for imaging in the visible spectral range from 400 to 700 nm for compatibility with molecular imaging applications as well as satellite and remote sensing. An 81 × 96 pixel spatial sampling density is achieved by using a custom-made fiber-optic bundle. The design considerations and fabrication aspects of the fiber bundle and imaging spectrometer are described in detail. Through the custom fiber bundle, the image of a scene of interest is collected and divided into discrete spatial groups, with spaces generated in between groups for spectral dispersion. This reorganized image is scaled down by an image taper for compatibility with following optical elements, dispersed by a prism, and is finally acquired by a CCD camera. To obtain an (x, y, λ) datacube from the snapshot measurement, a spectral calibration algorithm is executed for reconstruction of the spatial–spectral signatures of the observed scene. System characterization of throughput, resolution, and crosstalk was performed. Preliminary results illustrating changes in oxygen-saturation in an occluded human finger are presented to demonstrate the system’s capabilities.

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A review of snapshot multidimensional optical imaging: Measuring photon tags in parallel

Cited by 128 publications

References 232 publications

A Review of Ghost Imaging via Sparsity Constraints

A Review of Ghost Imaging via Sparsity Constraints

Bio-inspired imager improves sensitivity in near-infrared fluorescence image-guided surgery

High spatial sampling light-guide snapshot spectrometer

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