In this paper we consider the problem of reconstructing triangular surfaces from given contours. An algorithm solving this problem has to decide which contours of two successive slices should be connected by the surface (branching problem), and, given that, which vertices of the assigned contours should be connected for the triangular mesh (correspondence problem). We present a new approach that solves both tasks in an elegant way. The main idea is to employ discrete distance fields enhanced with correspondence information. This allows us not only to connect vertices from successive slices in a reasonable way but also to solve the branching problem by creating intermediate contours where adjacent contours differ too much. Last but not least we show how the 2D-distance fields used in the reconstruction step can be converted to a 3D-distance field that can be advantageously exploited for distance calculations during a subsequent simplification step.

https://cg.cs.uni-bonn.de/aigaion2root/attachments/klein-2000-reconstruction.pdf

Reconstruction and simplification of surfaces from contours

In this paper we consider the problem of reconstructing triangular surfaces from given contours. An algorithm solving this problem must decide which contours of two successive slices should be connected by the surface (branching problem) and, given that, which vertices of the assigned contours should be connected for the triangular mesh (correspondence problem). We present a new approach that solves both tasks in an elegant way. The main idea is to employ discrete distance fields enhanced with correspondence information. This allows us not only to connect vertices from successive slices in a reasonable way but also to solve the branching problem by creating intermediate contours where adjacent contours differ too much. Last but not least we show how the 2D distance fields used in the reconstruction step can be converted to a 3D distance field that can be advantageously exploited for distance calculations during a subsequent simplification step.

Reconstruction and Simplification of Surfaces from Contours

Background The stimulation and intragastric accumulation of gastric secretion has been recognized as an important factor in gastroesophageal reflux disease. However, the interaction of gastric secretion and meal emptying has not been fully understood. Current methods to assess gastric secretion are either invasive or unable to provide information on its volume, distribution and dynamics. The aim of this study was to quantify the interaction between meal emptying and meal induced gastric secretion by using quantitative magnetic resonance imaging (MRI) and pharmacokinetic analysis.



Methods  A chocolate test meal was developed which is secretion stimulating and MRI compatible. Meal emptying and gastric secretion were assessed in fourteen healthy volunteers using a validated quantitative MRI technique. A population based pharmacokinetic model was developed and applied to the extracted volume data, assessing the meal emptying rate, rate of secretion and their interaction.



Key Results  The test meal continuously induced gastric secretion in all subjects, which partly accumulated at the meal–air interface, forming a ‘secretion layer’ in the proximal stomach. Traditional fitting detected a significant correlation between meal emptying rate and rate of secretion. The pharmacokinetic model quantified this interaction and estimated a 2.3 ± 1 fold higher effect of meal on secretion than vice versa. The efficacy of the emptied meal to produce gastric secretion was 61%.



Conclusions & Inferences  The combined quantitative MRI and pharmacokinetic model approach allows for the quantification of gastric secretion volume and its interaction on meal emptying. The observed secretion layer might explain previous findings postulating the presence of an intragastric ‘acid pocket’.

https://www.zora.uzh.ch/id/eprint/66221/5/SauterM_etal_Neurogastroenterol_Motil_%282012%29.pdf

Measuring the interaction of meal and gastric secretion: a combined quantitative magnetic resonance imaging and pharmacokinetic modeling approach.

Image analysis and computer vision: 1999

Summary
•Quantification of overall growth and local growth zones in root system development is key to understanding the biology of plant growth, and thus to exploring the effects of environmental, genotypic and mutational variations on plant development and productivity.
•We introduce a methodology for analyzing growth patterns of plant roots from two-dimensional time series images, treating them as a spatio-temporal three-dimensional (3D) image volume. The roots are segmented from the images and then two types of analysis are performed: 3D spatio-temporal reconstruction analysis for simultaneous assessment of initiation and growth of multiple roots; and spatio-temporal pixel intensity analysis along root midlines for quantification of the growth zones.
•The test measurements show simultaneous emergence of basal roots but sequential emergence of lateral roots in Phaseolus vulgaris, while lateral roots of Cicer arietinum emerge in a rhythmic pattern. Local growth analysis reveals multimodal transient growth zone in basal roots. At the initial stages after emergence, the roots oscillate rapidly, which slows down with time.
•The methodology presented here allows detailed characterization of the phenomenology of roots, providing valuable information of spatio-temporal development, with applications in a wide range of growing plant organs.

https://nph.onlinelibrary.wiley.com/doi/pdf/10.1111/j.1469-8137.2012.04149.x

B. Parvin

Papers

An algebraic solution to surface recovery from cross-sectional contours