Onderzoek naar de dynamiek in het stedelijk geluidslandschap veroorzaakt door wegverkeer

Een recent gestart onderzoek aan de groep Akoestiek heeft tot doel de tijdsevolutie van verschillende geluidskarakteristieken te introduceren in de studie van stedelijke geluidslandschappen. Een micro-modellering van verkeersstromen wordt hierbij als basis gebruikt voor een nauwkeurige, dynamische modellering van de geluidsemissie veroorzaakt door verkeersstromen in steden. Deze dynamische emissie, gekoppeld aan een state of the art propagatiemodel, in ontwikkeling aan de onderzoeksgroep, laat vervolgens toe de tijdsvariatie in de geluisimmissie te evalueren. Het genereren van dynamische geluidskaarten, het berekenen van statistische geluidsniveau's, of het evalueren van ruimtelijke structuuringrepen behoort hiermee tot de mogelijkheden. A.d.h.v. van een aantal typesituaties zal de stand van het onderzoek worden toegelicht.

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Music in the urban soundscape?

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Renal Compartment Segmentation in DCE-MRI Images

Publication date: Available online 16 May 2016
Source:Medical Image Analysis
Author(s): Xin Yang, Hung Le Minh, Kwang-Ting (Tim) Cheng, Kyung Hyun Sung, Wenyu Liu
Renal compartment segmentation from Dynamic Contrast-Enhanced MRI (DCE-MRI) images is an important task for functional kidney evaluation. Despite advancement in segmentation methods, most of them focus on segmenting an entire kidney on CT images, there still lacks effective and automatic solutions for accurate segmentation of internal renal structures (i.e. cortex, medulla and renal pelvis) from DCE-MRI images. In this paper, we introduce a method for renal compartment segmentation which can robustly achieve high segmentation accuracy for a wide range of DCE-MRI data, and meanwhile requires little manual operations and parameter settings. The proposed method consists of five main steps. First, we pre-process the image time series to reduce the motion artifacts caused by the movement of the patients during the scans and enhance the kidney regions. Second, the kidney is segmented as a whole based on the concept of Maximally Stable Temporal Volume (MSTV). The proposed MSTV detects anatomical structures that are homogeneous in the spatial domain and stable in terms of temporal dynamics. MSTV-based kidney segmentation is robust to noises and does not require a training phase. It can well adapt to kidney shape variations caused by renal dysfunction. Third, voxels in the segmented kidney are described by principal components (PCs) to remove temporal redundancy and noises. And then k-means clustering of PCs is applied to separate voxels into multiple clusters. Fourth, the clusters are automatically labeled as cortex, medulla and pelvis based on voxels' geometric locations and intensity distribution. Finally, an iterative refinement method is introduced to further remove noises in each segmented compartment. Experiments on 14 real clinical kidney datasets and 12 synthetic dataset demonstrate that results produced by our method match very well with those segmented manually and the performance of our method is superior to the other five existing methods.

Graphical abstract

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Estimation of Fiber Orientations Using Neighborhood Information

Publication date: Available online 16 May 2016
Source:Medical Image Analysis
Author(s): Chuyang Ye, Jiachen Zhuo, Rao P. Gullapalli, Jerry L. Prince
Data from diffusion magnetic resonance imaging (dMRI) can be used to reconstruct fiber tracts, for example, in muscle and white matter. Estimation of fiber orientations (FOs) is a crucial step in the reconstruction process and these estimates can be corrupted by noise. In this paper, a new method called Fiber Orientation Reconstruction using Neighborhood Information (FORNI) is described and shown to reduce the effects of noise and improve FO estimation performance by incorporating spatial consistency. FORNI uses a fixed tensor basis to model the diffusion weighted signals, which has the advantage of providing an explicit relationship between the basis vectors and the FOs. FO spatial coherence is encouraged using weighted ℓ1-norm regularization terms, which contain the interaction of directional information between neighbor voxels. Data fidelity is encouraged using a squared error between the observed and reconstructed diffusion weighted signals. After appropriate weighting of these competing objectives, the resulting objective function is minimized using a block coordinate descent algorithm, and a straightforward parallelization strategy is used to speed up processing. Experiments were performed on a digital crossing phantom, ex vivo tongue dMRI data, and in vivo brain dMRI data for both qualitative and quantitative evaluation. The results demonstrate that FORNI improves the quality of FO estimation over other state of the art algorithms.

Graphical abstract

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Play in juvenile mink: litter effects, stability over time, and motivational heterogeneity

Abstract

Mink are potentially ideal for investigating the functions of play: deleterious effects of early social isolation suggest a crucial developmental role for play; and huge numbers of highly playful juvenile subjects can be studied on farms. We collected descriptive data on 186 pairs from 93 litters, half provided with play-eliciting environmental enrichment objects in their home cages, to test three hypotheses: (1) play frequency is subject to litter effects; (2) relative playfulness is stable over time; (3) play sub-types share a single, common motivational basis. We found weak litter effects that were driven by stronger litter effects on general activity, and weakly stable individual differences in both total and rough-and-tumble play. Experimentally increasing object play did not inhibit rough-and-tumble play, showing these sub-types are not motivational substitutes. Frequencies of these sub-types were also uncorrelated, and changed differently with time of day and age, further supporting this conclusion.

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Grounding Cognitive Control in Associative Learning

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Effects in the affect misattribution procedure are modulated by feature-specific attention allocation.

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