KEYWORDS: Image resolution, Time division multiplexing, Spatial resolution, 3D image processing, Image resolution, 3D acquisition, Digital holography, Microscopes, 3D displays
Tomographic diffractive microscopy allows for imaging unlabeled specimens, with a better resolution than conventional microscopes, giving access to the index of refraction distribution within the specimen, and possibly at high speed. Principles of image formation and reconstruction are presented, and progresses towards realtime, three-dimensional acquisition, image reconstruction and final display, are discussed, as well as towards three-dimensional isotropic-resolution imaging.
KEYWORDS: Visualization, Holograms, 3D image processing, 3D image reconstruction, Microscopy, 3D acquisition, Tomography, Time division multiplexing, Computer architecture, Image restoration
Phase microscopy techniques regained interest in allowing for the observation of unprepared specimens
with excellent temporal resolution. Tomographic diffractive microscopy is an extension of
holographic microscopy which permits 3D observations with a finer resolution than incoherent light
microscopes. Specimens are imaged by a series of 2D holograms: their accumulation progressively
fills the range of frequencies of the specimen in Fourier space. A 3D inverse FFT eventually provides
a spatial image of the specimen.
Consequently, acquisition then reconstruction are mandatory to produce an image that could prelude
real-time control of the observed specimen. The MIPS Laboratory has built a tomographic
diffractive microscope with an unsurpassed 130nm resolution but a low imaging speed - no less than
one minute. Afterwards, a high-end PC reconstructs the 3D image in 20 seconds. We now expect
an interactive system providing preview images during the acquisition for monitoring purposes.
We first present a prototype implementing this solution on CPU: acquisition and reconstruction are
tied in a producer-consumer scheme, sharing common data into CPU memory. Then we present
a prototype dispatching some reconstruction tasks to GPU in order to take advantage of SIMDparallelization
for FFT and higher bandwidth for filtering operations. The CPU scheme takes 6
seconds for a 3D image update while the GPU scheme can go down to 2 or > 1 seconds depending
on the GPU class. This opens opportunities for 4D imaging of living organisms or crystallization
processes. We also consider the relevance of GPU for 3D image interaction in our specific conditions.
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