We introduce Chromatix: an easy to use, open-source, differentiable wave optics simulation library. Engineered to fully exploit parallelism, from single CPU and GPU workstations to servers with multiple GPUs, Chromatix removes the computational scaling barrier for differentiable wave optics simulations. Chromatix allows for designing and optimizing a wide range of optical systems (e.g., tomography, light field microscopy, and ptychography) as well as solving inverse problems. We expect Chromatix to democratize and power the exploration of a rich design space in computational optics.
We have devised an innovative SIM imaging system to addresses these issues and achieves the following: (1) Aberration free super-Resolution Imaging: We introduce a hybrid adaptive optics system, TACO, correcting both illumination and excitation aberrations. This results in high-quality SIM super-resolution imaging even in highly aberrative environments. (2) Scalable multicolor Imaging: A dispersion compensation grating module was designed to correct the divergence of different excitation wavelength beams, enabling effortless increasement of color channels number with minimal realignment. (3) Multiplane 3D Imaging: Simultaneous multiplane imaging is achieved through a specialized multi-plane beam splitter. A deformable mirror facilitates rapid z-scan and aberration correction, ensuring fast, aberration-free volumetric imaging. (4) Automated Structure Decomposition: Our system adapts a convolutional neural network model with a novel architecture for automated decomposition of multiple cellular structures in a single channel. This innovation significantly broadens the application of SIM in complex high-dimensional data acquisition tasks.
PurposeSingle-energy computed tomography (CT) often suffers from poor contrast yet remains critical for effective radiotherapy treatment. Modern therapy systems are often equipped with both megavoltage (MV) and kilovoltage (kV) X-ray sources and thus already possess hardware for dual-energy (DE) CT. There is unexplored potential for enhanced image contrast using MV-kV DE-CT in radiotherapy contexts.ApproachA single-line integral toy model was designed for computing basis material signal-to-noise ratio (SNR) using estimation theory. Five dose-matched spectra (3 kV, 2 MV) and three variables were considered: spectral combination, spectral dose allocation, and object material composition. The single-line model was extended to a simulated CT acquisition of an anthropomorphic phantom with and without a metal implant. Basis material sinograms were computed and synthesized into virtual monoenergetic images (VMIs). MV-kV and kV-kV VMIs were compared with single-energy images.ResultsThe 80 kV-140 kV pair typically yielded the best SNRs, but for bone thicknesses >8 cm, the detunedMV-80 kV pair surpassed it. Peak MV-kV SNR was achieved with ∼90% dose allocated to the MV spectrum. In CT simulations of the pelvis with a steel implant, MV-kV VMIs yielded a higher contrast-to-noise ratio (CNR) than single-energy CT and kV-kV DE-CT. Without steel, the MV-kV VMIs produced higher contrast but lower CNR than single-energy CT.ConclusionsThis work analyzes MV-kV DE-CT imaging and assesses its potential advantages. The technique may be used for metal artifact correction and generation of VMIs with higher native contrast than single-energy CT. Improved denoising is generally necessary for greater CNR without metal.
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