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This paper presents the first volume visualization system that scales to petascale volumes imaged as a continuous stream of high-resolution electron microscopy images. Our architecture scales to dense, anisotropic petascale volumes because it: (1) decouples construction of the 3D multi-resolution representation required for visualization from data(More)
Surgical approaches tailored to an individual patient's anatomy and pathology have become standard in neurosurgery. Precise preoperative planning of these procedures, however, is necessary to achieve an optimal therapeutic effect. Therefore, multiple radiological imaging modalities are used prior to surgery to delineate the patient's anatomy, neurological(More)
Data sets imaged with modern electron microscopes can range from tens of terabytes to about one petabyte. Two new tools, Ssecrett and NeuroTrace, support interactive exploration and analysis of large-scale optical-and electron-microscopy images to help scientists reconstruct complex neural circuits of the mammalian nervous system.
Recent advances in scanning technology provide high resolution EM (electron microscopy) datasets that allow neuro-scientists to reconstruct complex neural connections in a nervous system. However, due to the enormous size and complexity of the resulting data, segmentation and visualization of neural processes in EM data is usually a difficult and very(More)
This paper presents ConnectomeExplorer, an application for the interactive exploration and query-guided visual analysis of large volumetric electron microscopy (EM) data sets in connectomics research. Our system incorporates a knowledge-based query algebra that supports the interactive specification of dynamically evaluated queries, which enable(More)
We propose a mixed-resolution volume ray-casting approach that enables more flexibility in the choice of down-sampling positions and filter kernels, allows freely mixing volume bricks of different resolutions during rendering, and does not require modifying the original sample values. A C 0-continuous function is obtained everywhere with hardware-native(More)
Recent advances in high-resolution microscopy let neuroscientists acquire neural-tissue volume data of extremely large sizes. However, the tremendous resolution and the high complexity of neural structures present big challenges to storage, processing, and visualization at interactive rates. A proposed system provides interactive exploration of petascale(More)
Proofreading refers to the manual correction of automatic segmentations of image data. In connectomics, electron microscopy data is acquired at nanometer-scale resolution and results in very large image volumes of brain tissue that require fully automatic segmentation algorithms to identify cell boundaries. However, these algorithms require hundreds of(More)
We present NeuroLines, a novel visualization technique designed for scalable detailed analysis of neuronal connectivity at the nanoscale level. The topology of 3D brain tissue data is abstracted into a multi-scale, relative distance-preserving subway map visualization that allows domain scientists to conduct an interactive analysis of neurons and their(More)
We introduce a new type of multi-resolution image pyramid for high-resolution images called <i>sparse pdf maps</i> (sPDF-maps). Each pyramid level consists of a sparse encoding of continuous probability density functions (pdfs) of pixel neighborhoods in the original image. The encoded pdfs enable the accurate computation of non-linear image operations(More)