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However, clinical use of fMRI is less widespread due to its complexity of imaging, image workflow, post-processing, and lack of algorithmic standards hindering result comparability.
Therefore, studies of leaf venation may continue to lag equivalent governmental or commercial methods by decades merely because the hardware needed to improve imaging and image workflow is expensive and because image analysis software tends to be either compiled and proprietary or composed of heterogeneous code snippets that are poorly documented or difficult to integrate with each other.
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Systems in radiation oncology or surgical navigation are likely not to accept compressed images, workflow concepts should reflect this.
Some examples of environmental applications taking advantage of the capabilities offered by parallel and distributed infrastructures are those using parameter estimation, model calibration (Vrugt et al. 2006; gSWAT 2011), Web Processing Service on the Grid (Giuliani et al. 2012), numerical weather prediction (Maity et al. (2013)) and satellite images workflows over the Grid (GreenLand 2011).
Open image in new window Fig. 1 The imaging workflow.
Within the context of the Rotterdam Scan Study, a standardized image analysis workflow is being developed, validated and applied to all imaging data, to enable the objective, accurate, and reproducible extraction of relevant parameters describing brain anatomy, possible brain pathologies, and structural and functional brain connectivity from multispectral MRI data.
Fig. 4 SAFEPOST image recognition workflow.
In the following, the different levels of image and workflow sharing are described.
Therefore, denoising data is often the first step of an image processing workflow.
Fig. 2 Collaborative image retrieval workflow based on the semi-supervised proposed framework.
Visualization libraries Visualizing images is an important component of the image processing workflow, used to inspect the final result and to adjust the parameters of intermediate processing operations.
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