Clinical classification of scoliosis patients using machine learning and markerless 3D surface trunk data.

Markerless 3D surface topography for scoliosis diagnosis and brace treatment can avoid repeated radiation known from standard X-ray analysis and possible side effects. Combined with the method of torso asymmetry analysis, curve severity and progression can be evaluated with high reliability. In the current study, a machine learning approach was utilised to classify scoliosis patients based on their trunk surface asymmetry pattern.

Innovative decision support for scoliosis brace therapy based on statistical modelling of markerless 3D trunk surface data.

Recently markerless 3D scanning methods receive an increased interest for therapy planning and brace treatment of patients with scoliosis. This avoids repeated radiation known from standard X-Ray analysis. Several authors introduced the method of asymmetry distance maps in order to classify curve severity and progression.

Workflow of CAD / CAM Scoliosis Brace Adjustment in Preparation Using 3D Printing.

Background: High correction bracing is the most effective conservative treatment for patients with scoliosis during growth. Still today braces for the treatment of scoliosis are made by casting patients while computer aided design (CAD) and computer aided manufacturing (CAM) is available with all possibilities to standardize pattern specific brace treatment and improve wearing comfort.

Objective: CAD / CAM brace production mainly relies on carving a polyurethane foam model which is the basis for vacuuming a polyethylene (PE) or polypropylene (PP) brace.

A phenomenological approach shows a high coherence of warming patterns in dimictic aquatic systems across latitude.

To predict the coherence in local responses to large-scale climatic forcing among aquatic systems, we developed a generalized approach to compare long-term data of dimictic water bodies based on phenomenologically defined hydrographic events. These climate-sensitive phases (inverse stratification, spring overturn, early thermal stratification, summer stagnation) were classified in a dual code (cold/warm) based on threshold temperatures. Accounting for a latitudinal gradient in seasonal timing of phases derived from gradients in cumulative irradiation (2.

Comparing in situ particle monitoring to microscopic counts of plankton in a drinking water reservoir.

In a one-year study, the multispecies assemblages of phytoplankton (picoplankton to microplankton) within a drinking water reservoir were counted, determined and evaluated in their size fractions using microscope enumeration (MC). The manual counts were compared with the size evaluation obtained by a light obscuring particle counter (PC) in order to evaluate its use for the monitoring practice of a drinking water reservoir. With this multispecies comparison we present a novel approach for the evaluation of automated counting systems.

Identifying cardinal dates in phytoplankton time series to enable the analysis of long-term trends.

Phenology and seasonal succession in aquatic ecosystems are strongly dependent on physical factors. In order to promote investigations into this coupling, methods of characterising annual time series of phytoplankton were derived and applied to a 31-year data set from Saidenbach Reservoir (Saxony, Germany). Field data are often scarce and irregularly sampled, particularly in the transition period from winter to spring, so reliable methods of determining cardinal dates in the time series are necessary.

Response of drinking-water reservoir ecosystems to decreased acidic atmospheric deposition in SE Germany: trends of chemical reversal.

This study evaluates chemical trends of seven acidified reservoirs and 22 tributaries in the Erzgebirge from 1993 to 2003. About 85% of these waters showed significantly (p < 0.05) declining concentrations of protons (-69%), nitrate (-41%), sulfate (-27%), and reactive aluminum (-50% on average).