The Topology ToolKit

This system paper presents the Topology ToolKit (TTK), a software platform designed for topological data analysis in scientific visualization. TTK provides a unified, generic, efficient, and robust implementation of key algorithms for the topological analysis of scalar data, including: critical points, integral lines, persistence diagrams, persistence curves, merge trees, contour trees, Morse-Smale complexes, fiber surfaces, continuous scatterplots, Jacobi sets, Reeb spaces, and more. TTK is easily accessible to end users due to a tight integration with ParaView. It is also easily accessible to developers through a variety of bindings (Python, VTK/C++) for fast prototyping or through direct, dependence-free, C++, to ease integration into pre-existing complex systems. While developing TTK, we faced several algorithmic and software engineering challenges, which we document in this paper. In particular, we present an algorithm for the construction of a discrete gradient that complies to the critical points extracted in the piecewise-linear setting. This algorithm guarantees a combinatorial consistency across the topological abstractions supported by TTK, and importantly, a unified implementation of topological data simplification for multi-scale exploration and analysis. We also present a cached triangulation data structure, that supports time efficient and generic traversals, which self-adjusts its memory usage on demand for input simplicial meshes and which implicitly emulates a triangulation for regular grids with no memory overhead. Finally, we describe an original software architecture, which guarantees memory efficient and direct accesses to TTK features, while still allowing for researchers powerful and easy bindings and extensions. TTK is open source (BSD license) and its code, online documentation and video tutorials are available on TTK's website

Fiber surfaces: generalizing isosurfaces to bivariate data

Scientific visualization has many effective methods for examining and exploring scalar and vector fields, but rather fewer for bivariate fields. We report the first general purpose approach for the interactive extraction of geometric separating surfaces in bivariate fields. This method is based on fiber surfaces: surfaces constructed from sets of fibers, the multivariate analogues of isolines. We show simple methods for fiber surface definition and extraction. In particular, we show a simple and efficient fiber surface extraction algorithm based on Marching Cubes. We also show how to construct fiber surfaces interactively with geometric primitives in the range of the function. We then extend this to build user interfaces that generate parameterized families of fiber surfaces with respect to arbitrary polygons. In the special case of isovalue-gradient plots, fiber surfaces capture features geometrically for quantitative analysis that have previously only been analysed visually and qualitatively using multi-dimensional transfer functions in volume rendering. We also demonstrate fiber surface extraction on a variety of bivariate data

Distributions of Roosting Sandhill Cranes as Identified by Aerial Thermography

We used aerial thermography to determine the location of sandhill crane (Grus canadensis) roosting sites during a single night over a 142-km reach of the Platte River, Nebraska. We assessed the influences of human disturbance features, screening of disturbance features by woody vegetation, distance to surrounding cropland of various types and channel width on distribution patterns of sandhill crane roosting sites with the aid of a geographic information system (GIS). We found that roosting sites were farther from bridges and paved roads than random points along the river channel; a visual woody screen mitigated the effect of bridges on locations of roosting sites; and roosting sites were in wider river channels than were observed at random points

Une nouvelle voie d'abord pour la neurolyse endoscopique du nerf suprascapulaire à l'incisure spinoglénoïdale : étude cadavérique préliminaire

International audienceThe suprascapular nerve (SSN) can become compressed at its 2 scapular attachments: the suprascapular and the spinoglenoid notch. The objective of this study was to describe a new arthroscopic approach for SSN neurolysis at the spinoglenoid notch. Ten cadaver shoulders were used. Two were dissected to simulate the “classical” arthroscopic approach and to help in the creation of a new “direct medial retrospinal” approach. Eight other shoulders were used to validate this new approach, with control of the whole juxta-glenoid course of the SSN as criterion of success. The retrospinal posterior approach allowed the entire juxta-glenoid segment of the SSN to be explored in 6 cases out of 8. One exploration was incomplete, another not feasible. SSN neurolysis at the spinoglenoid notch was feasible in cadavers on a retrospinal approach. © 2017 Elsevier Masson SASIntroduction Le nerf suprascapulaire (NSS) peut être comprimé à ses 2 points de fixation scapulaire : incisure suprascapulaire et incisure spinoglénoïdale (ISG). L’objectif de ce travail est de décrire un nouvel abord endoscopique pour la neurolyse du NSS à l’ISG.Méthode Dix épaules ont été utilisées. Deux épaules ont été disséquées pour simuler le trajet des voies d’abord endoscopiques « classiques » et aider à la création d’une nouvelle voie dite « médiale rétrospinale directe ». Huit autres épaules ont permis de valider cette nouvelle voie avec comme critère de réussite le contrôle de la totalité du trajet juxtaglénoïdien du NSS.Résultats La voie postérieure rétrospinale a permis d’explorer tout le segment juxtaglénoïdien du NSS dans 6 cas sur 8. Une exploration a été incomplète, une autre non réalisable.Conclusion La neurolyse du NSS à l’ISG est possible sur cadavre par l’utilisation d’une voie rétrospinale