scholarly journals FMRIPrep: a robust preprocessing pipeline for functional MRI

2018 ◽  
Author(s):  
Oscar Esteban ◽  
Christopher J. Markiewicz ◽  
Ross W. Blair ◽  
Craig A. Moodie ◽  
A. Ilkay Isik ◽  
...  
Keyword(s):  
Functional Mri ◽  
Ad Hoc ◽  
Visual Assessment ◽  
Fmri Data ◽  
High Quality ◽  
Qualitative Comparison ◽  
Integration Framework ◽  
Manual Intervention ◽  
Iterative Integration ◽  
Processing Techniques

Preprocessing of functional MRI (fMRI) involves numerous steps to clean and standardize data before statistical analysis. Generally, researchers create ad hoc preprocessing workflows for each new dataset, building upon a large inventory of tools available for each step. The complexity of these workflows has snowballed with rapid advances in MR data acquisition and image processing techniques. We introduce fMRIPrep, an analysis-agnostic tool that addresses the challenge of robust and reproducible preprocessing for task-based and resting fMRI data. FMRIPrep automatically adapts a best-in-breed workflow to the idiosyncrasies of virtually any dataset, ensuring high-quality preprocessing with no manual intervention. By introducing visual assessment checkpoints into an iterative integration framework for software-testing, we show that fMRIPrep robustly produces high-quality results on a diverse fMRI data collection comprising participants from 54 different studies in the OpenfMRI repository. We review the distinctive features of fMRIPrep in a qualitative comparison to other preprocessing workflows. We demonstrate that fMRIPrep achieves higher spatial accuracy as it introduces less uncontrolled spatial smoothness than commonly used preprocessing tools. FMRIPrep has the potential to transform fMRI research by equipping neuroscientists with a high-quality, robust, easy-to-use and transparent preprocessing workflow which can help ensure the validity of inference and the interpretability of their results.

Continuous and Progressive XML Query Processing and its Applications

2010 ◽  
pp. 181-197
Author(s):  
Stéphane Bressan ◽  
Wee Hyong Tok ◽  
Xue Zhao
Keyword(s):  
Query Processing ◽  
Data Streams ◽  
Ad Hoc ◽  
Data Representation ◽  
Future Trends ◽  
Xml Query Processing ◽  
Processing Techniques ◽  
Xml Technologies ◽  
State Of Art ◽  
Open Issues

Since XML technologies have become a standard for data representation, a great amount of discussion has been generated by the persisting open issues and their possible solutions. In this chapter, the authors consider the design space for XML query processing techniques that can handle ad hoc and continuous XPath or XQuery queries over XML data streams. This chapter presents the state-of-art techniques in continuous and progressive XML query processing. They also discuss several open issues and future trends.

scholarly journals Joint inversion of proxy system models to reconstruct paleoenvironmental time series from heterogeneous data

2020 ◽  
Vol 16 (1) ◽  
pp. 65-78 ◽  
Author(s):  
Gabriel J. Bowen ◽  
Brenden Fischer-Femal ◽  
Gert-Jan Reichart ◽  
Appy Sluijs ◽  
Caroline H. Lear
Keyword(s):  
Time Series ◽  
Ad Hoc ◽  
Joint Inversion ◽  
Environmental Variable ◽  
Heterogeneous Data ◽  
Published Data ◽  
Model Parameters ◽  
Qualitative Comparison ◽  
Bayesian Hierarchical ◽  
Proxy Reconstructions

Abstract. Paleoclimatic and paleoenvironmental reconstructions are fundamentally uncertain because no proxy is a direct record of a single environmental variable of interest; all proxies are indirect and sensitive to multiple forcing factors. One productive approach to reducing proxy uncertainty is the integration of information from multiple proxy systems with complementary, overlapping sensitivity. Mostly, such analyses are conducted in an ad hoc fashion, either through qualitative comparison to assess the similarity of single-proxy reconstructions or through step-wise quantitative interpretations where one proxy is used to constrain a variable relevant to the interpretation of a second proxy. Here we propose the integration of multiple proxies via the joint inversion of proxy system and paleoenvironmental time series models in a Bayesian hierarchical framework. The “Joint Proxy Inversion” (JPI) method provides a statistically robust approach to producing self-consistent interpretations of multi-proxy datasets, allowing full and simultaneous assessment of all proxy and model uncertainties to obtain quantitative estimates of past environmental conditions. Other benefits of the method include the ability to use independent information on climate and environmental systems to inform the interpretation of proxy data, to fully leverage information from unevenly and differently sampled proxy records, and to obtain refined estimates of proxy model parameters that are conditioned on paleo-archive data. Application of JPI to the marine Mg∕Ca and δ18O proxy systems at two distinct timescales demonstrates many of the key properties, benefits, and sensitivities of the method, and it produces new, statistically grounded reconstructions of Neogene ocean temperature and chemistry from previously published data. We suggest that JPI is a universally applicable method that can be implemented using proxy models of wide-ranging complexity to generate more robust, quantitative understanding of past climatic and environmental change.

Towards Selective Volumetric Additive Manufacturing and Processing of Ceramics

2019 ◽  
Author(s):  
A. P. Iliopoulos ◽  
J. G. Michopoulos ◽  
J. C. Steuben ◽  
A. J. Birnbaum ◽  
B. D. Graber ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Ceramic Powder ◽  
Ceramic Materials ◽  
High Quality ◽  
Analysis And Design ◽  
Spatially Resolved ◽  
Selective Approach ◽  
Scientists And Engineers ◽  
Processing Techniques ◽  
Am Processes

Abstract The development of advanced additive manufacturing (AM) and material processing techniques is currently a topic of great interest to broad communities of scientists and engineers. In particular, there is a need for AM processes capable of producing functional and high-quality components at a faster rate than is currently achievable. In response to this demand, the present work introduces the initial steps of a novel spatially-resolved and selective approach for processing volumetric regions of ceramic materials. The proposed method utilizes microwave radiation to heat material at desired locations within a domain filled with ceramic powder. Using this principle of operation, a number of methods for implementation of this process are proposed. As a first step, a multiphysics computational methodology and an associated model that allows for the analysis and design of relevant processing systems is introduced. Additionally, a number of simulations demonstrating the feasibility of the proposed methodology are presented. Based on these preliminary results, we conclude with a discussion of ongoing and future efforts to fully realize this technology.

Generating High-Quality Air-Coupled Ultrasonic Images for Wooden Material Characterization by Single Image Super-Resolution

2019 ◽  
Vol 34 (03) ◽  
pp. 2054008
Author(s):  
Lujun Lin ◽  
Yiming Fang ◽  
Xiaochen Du ◽  
Zhu Zhou
Keyword(s):  
Image Quality ◽  
Super Resolution ◽  
Visual Assessment ◽  
Wood Products ◽  
Superior Performance ◽  
Single Image ◽  
High Quality ◽  
Practical Applications ◽  
Image Super Resolution ◽  
Single Image Super Resolution

As the practical applications in other fields, high-resolution images are usually expected to provide a more accurate assessment for the air-coupled ultrasonic (ACU) characterization of wooden materials. This paper investigated the feasibility of applying single image super-resolution (SISR) methods to recover high-quality ACU images from the raw observations that were constructed directly by the on-the-shelf ACU scanners. Four state-of-the-art SISR methods were applied to the low-resolution ACU images of wood products. The reconstructed images were evaluated by visual assessment and objective image quality metrics, including peak signal-to-noise-ratio and structural similarity. Both qualitative and quantitative evaluations indicated that the substantial improvement of image quality can be yielded. The results of the experiments demonstrated the superior performance and high reproducibility of the method for generating high-quality ACU images. Sparse coding based super-resolution and super-resolution convolutional neural network (SRCNN) significantly outperformed other algorithms. SRCNN has the potential to act as an effective tool to generate higher resolution ACU images due to its flexibility.

Marine CSEM of the Scarborough gas field, Part 1: Experimental design and data uncertainty

Geophysics ◽  
2012 ◽  
Vol 77 (4) ◽  
pp. E281-E299 ◽  
Author(s):  
David Myer ◽  
Steven Constable ◽  
Kerry Key ◽  
Michael E. Glinsky ◽  
Guimin Liu
Keyword(s):  
Perturbation Analysis ◽  
Data Uncertainty ◽  
Quality Data ◽  
High Quality ◽  
Gas Field ◽  
Data Set ◽  
Resistive Layer ◽  
Mapping Tool ◽  
Marine Csem ◽  
Processing Techniques

We describe the planning, processing, and uncertainty analysis for a marine CSEM survey of the Scarborough gas field off the northwest coast of Australia, consisting of 20 transmitter tow lines and 144 deployments positioned along a dense 2D profile and a complex 3D grid. The purpose of this survey was to collect a high-quality data set over a known hydrocarbon prospect and use it to further the development of CSEM as a hydrocarbon mapping tool. Recent improvements in navigation and processing techniques yielded high-quality frequency domain data. Data pseudosections exhibit a significant anomaly that is laterally confined within the known reservoir location. Perturbation analysis of the uncertainties in the transmitter parameters yielded predicted uncertainties in amplitude and phase of just a few percent at close ranges. These uncertainties may, however, be underestimated. We introduce a method for more accurately deriving uncertainties using a line of receivers towed twice in opposite directions. Comparing the residuals for each line yields a Gaussian distribution directly related to the aggregate uncertainty of the transmitter parameters. Constraints on systematic error in the transmitter antenna dip and inline range can be calculated by perturbation analysis. Uncertainties are not equal in amplitude and phase, suggesting that inversion of these data would be better suited in these components rather than in real and imaginary components. One-dimensional inversion showed that the reservoir and a confounding resistive layer above it cannot be separately resolved even when the roughness constraint is modified to allow for jumps in resistivity and prejudices are provided, indicating that this level of detail is beyond the single-site CSEM data. Further, when range-dependent error bars are used, the resolution decreases at a shallower depth than when a fixed-error level is used.

scholarly journals Decoding of generic mental representations from functional MRI data using word embeddings

2016 ◽  
Author(s):  
Francisco Pereira ◽  
Bin Lou ◽  
Brianna Pritchett ◽  
Nancy Kanwisher ◽  
Matthew Botvinick ◽  
...  
Keyword(s):  
Functional Mri ◽  
Semantic Information ◽  
Mental Representations ◽  
Fmri Data ◽  
Word Embeddings ◽  
Imaging Data ◽  
Forward Models ◽  
Complex Stimuli

AbstractSeveral different groups have demonstrated the feasibility of building forward models of functional MRI data in response to concrete stimuli such as pictures or video, and of using these models to decode or reconstruct stimuli shown while acquiring test fMRI data. In this paper, we introduce an approach for building forward models of conceptual stimuli, concrete or abstract, and for using these models to carry out decoding of semantic information from new imaging data. We show that this approach generalizes to topics not seen in training, and provides a straightforward path to decoding from more complex stimuli such as sentences or paragraphs.

scholarly journals Attenuation of Motion Artifacts in fMRI using Discrete Reconstruction of Irregular fMRI Trajectories (DRIFT)

2019 ◽  
Author(s):  
David Parker ◽  
Qolamreza Razlighi
Keyword(s):  
Motion Correction ◽  
Pulse Sequence ◽  
Hybrid Approach ◽  
Simulated Data ◽  
Bloch Equation ◽  
Motion Artifacts ◽  
Fmri Data ◽  
Out Of Plane ◽  
Motion Problem ◽  
Processing Techniques

AbstractNumerous studies reported motion as the most detrimental source of noise and artifacts in functional magnetic resonance imaging (fMRI). Different approaches have been proposed and used to attenuate the effect of motion on fMRI data, including both prospective and retrospective (post-processing) techniques. However, each type of motion (e.g. translation versus rotation or in-plane versus out-of-plane) has a distinct effect on the MR signal, which is not fully understood nor appropriately modeled in the field. In addition, effects of the same motion can be substantially different depending on when it occurs during the pulse sequence (e.g. RF excitation, gradient encoding, or k-space read-out). Thus, each distinct kind of motion and the time of its occurrence may require a unique approach to be optimally corrected. Therefore, we start with an investigation of the effects of different motions on the MR signal based on the Bloch equation. We then simulate their unique effects with a comprehensive fMRI simulator. Our results indicate that current motion correction methods fail to completely address the motion problem. Retrospective techniques such as spatial realignment can correct for between-volume misalignment, but fail to address within volume contamination and spin-history artifacts. Because of the steady state nature of the fMRI acquisition, spin-history artifacts arising from over/under excitation during slice-selection causes the motion artifacts to contaminate MR signal even after cessation of motion, which makes it challenging to be corrected retrospectively. Prospective motion correction has been proposed to prevent spin-history artifacts, but fails to address motion artifacts during k-space readout. In this article, we propose a novel method to remove these artifacts: Discrete reconstruction of irregular fMRI trajectory (DRIFT). Our method calculates the exact displacement of k-space recording due to motion at each dwell time and retrospectively corrects each slice of the fMRI volume using an inverse nonuniform Fourier transform. We evaluate our proposed methods using simulated data as well as fMRI data collected from a rotating phantom inside a 3T Siemens Prisma scanner. We conclude that a hybrid approach with both prospective and retrospective components are essentially required for optimal removal of motion artifacts from the fMRI data.

scholarly journals A Survey of TDMA-based MAC Protocols for Vehicular Ad Hoc Networks

2019 ◽  
Vol 8 (5C) ◽  
pp. 1247-1259
Keyword(s):  
Access Control ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Mac Protocols ◽  
Media Access Control ◽  
Media Access ◽  
Medium Access Control Protocols ◽  
Medium Access ◽  
Open Problems ◽  
Qualitative Comparison

MAC design in a vehicle network is a challenging task due to high node speed, frequent topology changes, lack of infrastructure, and different QoS requirements. Several medium access control protocols based on Time Division Multiple Access (TDMA) have recently been suggested for VANETs in an effort to guarantee that all cars have sufficient time to send safety messages without collisions and to decrease the end-to-end delay and the loss ratio of packets. The reasons for using the collision-free media access control paradigm in VANETs are identified in this document. We then present a new topology-based classification and provide an overview of the MAC protocols suggested for VANETs based on TDMA. We concentrate on these protocols ' features as well as their advantages and constraints. Finally, we provide a qualitative comparison and address some open problems that need to be addressed in future studies to enhance the efficiency of TDMA-based MAC protocols for vehicle-to-vehicle (V2V) and vehicle to infrastructural (V2I) communications.

Sign in / Sign up

Export Citation Format

Share Document