3D real-time visualization of blood flow in cerebral aneurysms by light field particle image velocimetry

Carlsohn, Matthias F.; Kemmling, André; Petersen, Arne; Wietzke, Lennart

doi:10.1117/12.2220417

Cited by 11 publications

(9 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…which is exactly the unit-magnification incoherent image obtained in the case of lensless ghost imaging [40,46], whose point-spread function is determined by the squared Fourier transform of the source intensity profile. In the geometrical optics limit (k → ∞), the dominant contribution to the integral (19) comes from the stationary point of the real and imaginary parts of the exponent, yielding…”

Section: Iii2 Analysis Of Setup1mentioning

confidence: 99%

“…Plenoptic imaging is currently employed in a very wide range of applications, that include stereoscopy [1, 4,5], microscopy [6][7][8][9], particle image velocimetry [10], particle tracking and sizing [11], and wavefront sensing [12][13][14][15]. Since plenoptic devices are able to simultaneously acquire 2D images from multiple perspectives, they are considered among the fastest and most promising methods for 3D imaging [16], as shown by the very recent use in imaging of animal neuronal activity [9], surgical robotics [17], endoscopy [18] and blood-flow visualization [19].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Signal-to-noise properties of correlation plenoptic imaging with chaotic light

et al. 2019

View full text Add to dashboard Cite

Correlation Plenoptic Imaging (CPI) is a novel imaging technique, that exploits the correlations between the intensity fluctuations of light to perform the typical tasks of plenoptic imaging (namely, refocusing out-of-focus parts of the scene, extending the depth of field, and performing 3D reconstruction), without entailing a loss of spatial resolution. Here, we consider two different CPI schemes based on chaotic light, both employing ghost imaging: the first one to image the object, the second one to image the focusing element. We characterize their noise properties in terms of the signalto-noise ratio (SNR) and compare their performances. We find that the SNR can be significantly higher and easier to control in the second CPI scheme, involving standard imaging of the object; under adequate conditions, this scheme enables reducing by one order of magnitude the number of frames for achieving the same SNR.

show abstract

Section: Iii2 Analysis Of Setup1mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Signal-to-noise properties of correlation plenoptic imaging with chaotic light

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Indeed, high-speed and large-scale 3D functional imaging of neuronal activity has been demonstrated [7]. Furthermore, first studies for surgical robotics [17], endoscopic application [18] and blood-flow visualization [19] have been performed.The key component of standard plenoptic cameras is a microlens array inserted in the native image plane, that reproduces repeated images of the main camera lens on the sensor behind it [1,15]. This enables reconstruction of light paths, employed, in post-processing, for refocusing different planes, changing point of view and extending depth of field (DOF) within the acquired image.…”

mentioning

confidence: 99%

mentioning

confidence: 99%

Diffraction-Limited Plenoptic Imaging with Correlated Light

et al. 2017

View full text Add to dashboard Cite

Traditional optical imaging faces an unavoidable trade-off between resolution and depth of field (DOF). To increase resolution, high numerical apertures (NA) are needed, but the associated large angular uncertainty results in a limited range of depths that can be put in sharp focus. Plenoptic imaging was introduced a few years ago to remedy this trade off. To this aim, plenoptic imaging reconstructs the path of light rays from the lens to the sensor. However, the improvement offered by standard plenoptic imaging is practical and not fundamental: the increased DOF leads to a proportional reduction of the resolution well above the diffraction limit imposed by the lens NA. In this paper, we demonstrate that correlation measurements enable pushing plenoptic imaging to its fundamental limits of both resolution and DOF. Namely, we demonstrate to maintain the imaging resolution at the diffraction limit while increasing the depth of field by a factor of 7. Our results represent the theoretical and experimental basis for the effective development of the promising applications of plenoptic imaging.Plenoptic imaging (PI) is a novel optical method for recording visual information [1]. Its peculiarity is the ability to record both position and propagation direction of light in a single exposure. PI is currently employed in the most diverse applications, from stereoscopy [1][2][3], to microscopy [4][5][6][7], particle image velocimetry [8], particle tracking and sizing [9], wavefront sensing [10][11][12][13] and photography, where it currently enables digital cameras with refocusing capabilities [14,15]. The capability of PI to simultaneously acquire multiple-perspective 2D images brings it among the fastest and most promising methods for 3D imaging with the available technologies [16]. Indeed, high-speed and large-scale 3D functional imaging of neuronal activity has been demonstrated [7]. Furthermore, first studies for surgical robotics [17], endoscopic application [18] and blood-flow visualization [19] have been performed.The key component of standard plenoptic cameras is a microlens array inserted in the native image plane, that reproduces repeated images of the main camera lens on the sensor behind it [1,15]. This enables reconstruction of light paths, employed, in post-processing, for refocusing different planes, changing point of view and extending depth of field (DOF) within the acquired image. However, a fundamental trade-off between spatial and angular resolution is naturally built in standard plenoptic imaging. If N tot is the total number of pixels per line on the sensor, N x the number of microlenses per line, and N u the number of pixels per line associated with each microlens, then N x N u = N tot . Essentially, standard PI gives the same resolution and DOF one would obtain with a N u times smaller NA. The final advantage is thus practical rather than fundamental, and is limited * francesco.pepe@ba.infn.it † milena.dangelo@uniba.it to higher luminosity (hence SNR) of the final image and parallel acquisition of m...

show abstract

“…Despite its limitation, PI is currently employed in the most diverse applications, including 3D imaging and sensing [5,22], stereoscopy [2,23,24], particle image velocimetry [25], particle tracking and sizing [26], wavefront sensing [6,[27][28][29], microscopy [4,6,11,30] and digital cameras with refocusing capabilities [31]. Plenoptic imaging has also been employed in surgical robotics [32], endoscopic applications [33], and blood-flow visualization [34].…”

Section: Introductionmentioning

confidence: 99%

Correlation Plenoptic Imaging: An Overview

et al. 2018

View full text Add to dashboard Cite

Plenoptic imaging (PI) enables refocusing, depth-of-field (DOF) extension and 3D visualization, thanks to its ability to reconstruct the path of light rays from the lens to the image. However, in state-of-the-art plenoptic devices, these advantages come at the expenses of the image resolution, which is always well above the diffraction limit defined by the lens numerical aperture (NA). To overcome this limitation, we have proposed exploiting the spatio-temporal correlations of light, and to modify the ghost imaging scheme by endowing it with plenoptic properties. This approach, named Correlation Plenoptic Imaging (CPI), enables pushing both resolution and DOF to the fundamental limit imposed by wave-optics. In this paper, we review the methods to perform CPI both with chaotic light and with entangled photon pairs. Both simulations and a proof-of-principle experimental demonstration of CPI will be presented.

show abstract

3D real-time visualization of blood flow in cerebral aneurysms by light field particle image velocimetry

Cited by 11 publications

References 6 publications

Signal-to-noise properties of correlation plenoptic imaging with chaotic light

Signal-to-noise properties of correlation plenoptic imaging with chaotic light

Diffraction-Limited Plenoptic Imaging with Correlated Light

Correlation Plenoptic Imaging: An Overview

Contact Info

Product

Resources

About