38-Issue 3

Permanent URI for this collection

https://diglib.eg.org/handle/10.2312/2632780

Browse

Browsing 38-Issue 3 by Author "Agus, Marco"

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    A Framework for GPU-accelerated Exploration of Massive Time-varying Rectilinear Scalar Volumes
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Marton, Fabio; Agus, Marco; Gobbetti, Enrico; Gleicher, Michael and Viola, Ivan and Leitte, Heike
    We introduce a novel flexible approach to spatiotemporal exploration of rectilinear scalar volumes. Our out-of-core representation, based on per-frame levels of hierarchically tiled non-redundant 3D grids, efficiently supports spatiotemporal random access and streaming to the GPU in compressed formats. A novel low-bitrate codec able to store into fixed-size pages a variable-rate approximation based on sparse coding with learned dictionaries is exploited to meet stringent bandwidth constraint during time-critical operations, while a near-lossless representation is employed to support high-quality static frame rendering. A flexible high-speed GPU decoder and raycasting framework mixes and matches GPU kernels performing parallel object-space and image-space operations for seamless support, on fat and thin clients, of different exploration use cases, including animation and temporal browsing, dynamic exploration of single frames, and high-quality snapshots generated from near-lossless data. The quality and performance of our approach are demonstrated on large data sets with thousands of multi-billion-voxel frames.
  • Thumbnail Image
    Item
    Interactive Volumetric Visual Analysis of Glycogen-derived Energy Absorption in Nanometric Brain Structures
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Agus, Marco; Calì, Corrado; Al-Awami, Ali K.; Gobbetti, Enrico; Magistretti, Pierre J.; Hadwiger, Markus; Gleicher, Michael and Viola, Ivan and Leitte, Heike
    Digital acquisition and processing techniques are changing the way neuroscience investigation is carried out. Emerging applications range from statistical analysis on image stacks to complex connectomics visual analysis tools targeted to develop and test hypotheses of brain development and activity. In this work, we focus on neuroenergetics, a field where neuroscientists analyze nanoscale brain morphology and relate energy consumption to glucose storage in form of glycogen granules. In order to facilitate the understanding of neuroenergetic mechanisms, we propose a novel customized pipeline for the visual analysis of nanometric-level reconstructions based on electron microscopy image data. Our framework supports analysis tasks by combining i) a scalable volume visualization architecture able to selectively render image stacks and corresponding labelled data, ii) a method for highlighting distance-based energy absorption probabilities in form of glow maps, and iii) a hybrid connectivitybased and absorption-based interactive layout representation able to support queries for selective analysis of areas of interest and potential activity within the segmented datasets. This working pipeline is currently used in a variety of studies in the neuroenergetics domain. Here, we discuss a test case in which the framework was successfully used by domain scientists for the analysis of aging effects on glycogen metabolism, extracting knowledge from a series of nanoscale brain stacks of rodents somatosensory cortex.