Single-shot hyperspectral multiplexed imaging using a computational imaging array (Conference Presentation)

2017 ◽  
Author(s):  
Joseph H. Lin
Keyword(s):  
Computational Imaging ◽  
Single Shot ◽  
Imaging Array ◽  
Multiplexed Imaging

scholarly journals Holographic optical field recovery using a regularized untrained deep decoder network

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Farhad Niknam ◽  
Hamed Qazvini ◽  
Hamid Latifi
Keyword(s):  
Computational Imaging ◽  
Training Dataset ◽  
Reconstruction Method ◽  
Single Shot ◽  
Sample Type ◽  
Lack Of Information ◽  
Image Prior ◽  
Measured Information ◽  
Image Priors ◽  
Training Resources

AbstractImage reconstruction using minimal measured information has been a long-standing open problem in many computational imaging approaches, in particular in-line holography. Many solutions are devised based on compressive sensing (CS) techniques with handcrafted image priors or supervised deep neural networks (DNN). However, the limited performance of CS methods due to lack of information about the image priors and the requirement of an enormous amount of per-sample-type training resources for DNNs has posed new challenges over the primary problem. In this study, we propose a single-shot lensless in-line holographic reconstruction method using an untrained deep neural network which is incorporated with a physical image formation algorithm. We demonstrate that by modifying a deep decoder network with simple regularizers, a Gabor hologram can be inversely reconstructed via a minimization process that is constrained by a deep image prior. The outcoming model allows to accurately recover the phase and amplitude images without any training dataset, excess measurements, or specific assumptions about the object’s or the measurement’s characteristics.

scholarly journals Holographic Optical Field Recovery Using a Regularized Untrained Deep Decoder Network

2021 ◽  
Author(s):  
Farhad Niknam ◽  
Hamed Ghazvini ◽  
Hamid Latifi
Keyword(s):  
Computational Imaging ◽  
Training Dataset ◽  
Reconstruction Method ◽  
Single Shot ◽  
Sample Type ◽  
Lack Of Information ◽  
Image Prior ◽  
Measured Information ◽  
Image Priors ◽  
Training Resources

Abstract Image reconstruction using minimal measured information has been a long-standing open problem in many computational imaging approaches, in particular in-line holography. Many solutions are devised based on compressive sensing (CS) techniques with handcrafted image priors or supervised Deep Neural Networks (DNN). However, the limited performance of CS methods due to lack of information about the image priors and the requirement of an enormous amount of per-sample-type training resources for DNNs has posed new challenges over the primary problem. In this study, we propose a single-shot lensless in-line holographic reconstruction method using an untrained deep neural network which is incorporated with a physical image formation algorithm. We demonstrate that by modifying a deep decoder network with simple regularizers, a Gabor hologram can be inversely reconstructed via a minimization process that is constrained by a deep image prior. The outcoming model allows to accurately recover the phase and amplitude images without any training dataset, excess measurements, or specific assumptions about the object’s or the measurement’s characteristics.

scholarly journals Single-shot 3D wide-field fluorescence imaging with a Computational Miniature Mesoscope

2020 ◽  
Vol 6 (43) ◽  
pp. eabb7508
Author(s):  
Yujia Xue ◽  
Ian G. Davison ◽  
David A. Boas ◽  
Lei Tian
Keyword(s):  
Light Emitting Diode ◽  
Lightweight Design ◽  
Three Dimensional ◽  
Microlens Array ◽  
Computational Imaging ◽  
Depth Of Field ◽  
Wide Field ◽  
Single Shot ◽  
Light Emitting ◽  
Imaging Capability

Fluorescence microscopes are indispensable to biology and neuroscience. The need for recording in freely behaving animals has further driven the development in miniaturized microscopes (miniscopes). However, conventional microscopes/miniscopes are inherently constrained by their limited space-bandwidth product, shallow depth of field (DOF), and inability to resolve three-dimensional (3D) distributed emitters. Here, we present a Computational Miniature Mesoscope (CM2) that overcomes these bottlenecks and enables single-shot 3D imaging across an 8 mm by 7 mm field of view and 2.5-mm DOF, achieving 7-μm lateral resolution and better than 200-μm axial resolution. The CM2 features a compact lightweight design that integrates a microlens array for imaging and a light-emitting diode array for excitation. Its expanded imaging capability is enabled by computational imaging that augments the optics by algorithms. We experimentally validate the mesoscopic imaging capability on 3D fluorescent samples. We further quantify the effects of scattering and background fluorescence on phantom experiments.

Functional stereotactic radiosurgery involving a dedicated linear accelerator and gamma unit: a comparison study

2004 ◽  
pp. 373-380 ◽  
Author(s):  
Timothy D. Solberg ◽  
Steven J. Goetsch ◽  
Michael T. Selch ◽  
William Melega ◽  
Goran Lacan ◽  
...  
Keyword(s):  
Stereotactic Radiosurgery ◽  
Linear Accelerator ◽  
Treatment Plan ◽  
Single Shot ◽  
Submillimeter Range ◽  
Primate Model ◽  
Content Type ◽  
Stereotactic Frame ◽  
Targeting Ability ◽  
Fine Print

Object. The purpose of this work was to investigate the targeting and dosimetric characteristics of a linear accelerator (LINAC) system dedicated for stereotactic radiosurgery compared with those of a commercial gamma knife (GK) unit. Methods. A phantom was rigidly affixed within a Leksell stereotactic frame and axial computerized tomography scans were obtained using an appropriate stereotactic localization device. Treatment plans were performed, film was inserted into a recessed area, and the phantom was positioned and treated according to each treatment plan. In the case of the LINAC system, four 140° arcs, spanning ± 60° of couch rotation, were used. In the case of the GK unit, all 201 sources were left unplugged. Radiation was delivered using 3- and 8-mm LINAC collimators and 4- and 8-mm collimators of the GK unit. Targeting ability was investigated independently on the dedicated LINAC by using a primate model. Measured 50% spot widths for multisource, single-shot radiation exceeded nominal values in all cases by 38 to 70% for the GK unit and 11 to 33% for the LINAC system. Measured offsets were indicative of submillimeter targeting precision on both devices. In primate studies, the appearance of an magnetic resonance imaging—enhancing lesion coincided with the intended target. Conclusions. Radiosurgery performed using the 3-mm collimator of the dedicated LINAC exhibited characteristics that compared favorably with those of a dedicated GK unit. Overall targeting accuracy in the submillimeter range can be achieved, and dose distributions with sharp falloff can be expected for both devices.

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