The HyTI (Hyperspectral Thermal Imager) mission, funded by NASA's Earth Science Technology Office InVEST (In-Space Validation of Earth Science Technologies) program, will demonstrate how high spectral and spatial longwave infrared image data can be acquired from a 6U CubeSat platform. The mission will use a spatially modulated interferometric imaging technique to produce spectro-radiometrically calibrated image cubes, with 25 channels between 8-10.7 m, at a ground sample distance of ~70 m. The HyTI performance model indicates narrow band NETs of <0.3 K. The small form factor of HyTI is made possible via the use of a no-moving-parts Fabry-Perot interferometer, and JPL's cryogenically-cooled BIRD FPA technology. Launch is scheduled for no earlier than October 2020. The value of HyTI to Earth scientists will be demonstrated via on-board processing of the raw instrument data to generate L1 and L2 products, with a focus on rapid delivery of precision agriculture metrics. .
a) (b) (c) (d) Fig. 1:Analysing and visualizing MRSI data in our system. Red brush selecting the originally drawn CE region by a user in a histogram (a). Green brush selecting voxels with CNR ≥ 2 depicting high tumour intensity (b). Yellow convex hull brush gathering similar voxels in a scatter plot relating NAA/Creatine and Choline/Creatine ratios (c). Multi-modal rendering of Axial view of MR T1 Gado with manually thresholded CNR ≥ 2, FLAIR, CNR color map and yellow, red and green segmentations obtained from the respective brushes (d).Abstract-For cancers such as glioblastoma multiforme, there is an increasing interest in defining "biological target volumes" (BTV), high tumour-burden regions which may be targeted with dose boosts in radiotherapy. The definition of a BTV requires insight into tumour characteristics going beyond conventionally defined radiological abnormalities and anatomical features. Molecular and biochemical imaging techniques, like positron emission tomography, the use of Magnetic Resonance (MR) Imaging contrast agents or MR Spectroscopy deliver this information and support BTV delineation. MR Spectroscopy Imaging (MRSI) is the only non-invasive technique in this list. Studies with MRSI have shown that voxels with certain metabolic signatures are more susceptible to predict the site of relapse. Nevertheless, the discovery of complex relationships between a high number of different metabolites, anatomical, molecular and functional features is an ongoing topic of research -still lacking appropriate tools supporting a smooth workflow by providing data integration and fusion of MRSI data with other imaging modalities. We present a solution bridging this gap which gives fast and flexible access to all data at once. By integrating a customized visualization of the multi-modal and multi-variate image data with a highly flexible visual analytics (VA) framework, it is for the first time possible to interactively fuse, visualize and explore user defined metabolite relations derived from MRSI in combination with markers delivered by other imaging modalities. Real-world medical cases demonstrate the utility of our solution. By making MRSI data available both in a VA tool and in a multi-modal visualization renderer we can combine insights from each side to arrive at a superior BTV delineation. We also report feedback from domain experts indicating significant positive impact in how this work can improve the understanding of MRSI data and its integration into radiotherapy planning.
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