De-Identification Technique with Facial Deformation in Head CT Images
AbstractHead CT, which includes the facial region, can visualize faces using 3D reconstruction, raising concern that individuals may be identified. We developed a new de-identification technique that distorts the faces of head CT images. Head CT images that were distorted were labeled as"original images" and the others as"reference images." Reconstructed face models of both were created, with 400 control points on the facial surfaces. All voxel positions in the original image were moved and deformed according to the deformation vectors required to move to corresponding control points on the reference im...
Source: Neuroinformatics - May 25, 2023 Category: Neuroscience Source Type: research
CellRemorph: A Toolkit for Transforming, Selecting, and Slicing 3D Cell Structures on the Road to Morphologically Detailed Astrocyte Simulations
AbstractUnderstanding functions of astrocytes can be greatly enhanced by building and simulating computational models that capture their morphological details. Novel computational tools enable utilization of existing morphological data of astrocytes and building models that have appropriate level of details for specific simulation purposes. In addition to analyzing existing computational tools for constructing, transforming, and assessing astrocyte morphologies, we present here the CellRemorph toolkit implemented as an add-on for Blender, a 3D modeling platform increasingly recognized for its utility for manipulating 3D bi...
Source: Neuroinformatics - May 3, 2023 Category: Neuroscience Source Type: research
Correction to: Building FAIR Functionality: Annotating Events in Time Series Data Using Hierarchical Event Descriptors (HED)
(Source: Neuroinformatics)
Source: Neuroinformatics - April 11, 2023 Category: Neuroscience Source Type: research
A Method for In-Vivo Mapping of Axonal Diameter Distributions in the Human Brain Using Diffusion-Based Axonal Spectrum Imaging (AxSI)
AbstractIn this paper we demonstrate a generalized and simplified pipeline called axonal spectrum imaging (AxSI) forin-vivo estimation of axonal characteristics in the human brain. Whole-brain estimation of the axon diameter,in-vivo andnon-invasively, across all fiber systems will allow exploring uncharted aspects of brain structure and function relations with emphasis on connectivity and connectome analysis. While axon diameter mapping is important in and of itself, its correlation with conduction velocity will allow, for the first time, the explorations of information transfer mechanisms within the brain. We demonstrate ...
Source: Neuroinformatics - April 10, 2023 Category: Neuroscience Source Type: research
Funcmasker-flex: An Automated BIDS-App for Brain Segmentation of Human Fetal Functional MRI data
AbstractFetal functional magnetic resonance imaging (fMRI) offers critical insight into the developing brain and could aid in predicting developmental outcomes. As the fetal brain is surrounded by heterogeneous tissue, it is not possible to use adult- or child-based segmentation toolboxes. Manually-segmented masks can be used to extract the fetal brain; however, this comes at significant time costs. Here, we present a new BIDS App for masking fetal fMRI,funcmasker-flex, that overcomes these issues with a robust 3D convolutional neural network (U-net) architecture implemented in an extensible and transparent Snakemake workf...
Source: Neuroinformatics - March 31, 2023 Category: Neuroscience Source Type: research
A Minimum Bayes Factor Based Threshold for Activation Likelihood Estimation
AbstractActivation likelihood estimation (ALE) is among the most used algorithms to perform neuroimaging meta-analysis. Since its first implementation, several thresholding procedures had been proposed, all referred to the frequentist framework, returning a rejection criterion for the null hypothesis according to the critical p-value selected. However, this is not informative in terms of probabilities of the validity of the hypotheses. Here, we describe an innovative thresholding procedure based on the concept of minimum Bayes factor (mBF). The use of the Bayesian framework allows to consider different levels of probabilit...
Source: Neuroinformatics - March 28, 2023 Category: Neuroscience Source Type: research
Analysis of Network Models with Neuron-Astrocyte Interactions
In this study, we analyze the evolution of these models and the biophysical, biochemical, cellular, and network mechanisms used to construct them. Based on our analysis, we propose how to systematically describe and categorize interaction schemes between cells in neuron-astrocyte networks. We additionally study the models in view of the existing experimental data and present future perspectives. Our analysis is an important first step towards understanding astrocytic contribution to brain functions. However, more advances are needed to collect comprehensive data about astrocyte morphology and physiology in vivo and to bett...
Source: Neuroinformatics - March 23, 2023 Category: Neuroscience Source Type: research
ABCD_Harmonizer: An Open-source Tool for Mapping and Controlling for Scanner Induced Variance in the Adolescent Brain Cognitive Development Study
AbstractData from multisite magnetic resonance imaging (MRI) studies contain variance attributable to the scanner that can reduce statistical power and potentially bias results if not appropriately managed. The Adolescent Cognitive Brain Development (ABCD) study is an ongoing, longitudinal neuroimaging study acquiring data from over 11,000 children starting at 9 –10 years of age. These scans are acquired on 29 different scanners of 5 different model types manufactured by 3 different vendors. Publicly available data from the ABCD study include structural MRI (sMRI) measures such as cortical thickness and diffusion MRI (d...
Source: Neuroinformatics - March 20, 2023 Category: Neuroscience Source Type: research
Automatic Detection of Alzheimer's Disease using Deep Learning Models and Neuro-Imaging: Current Trends and Future Perspectives
This study examines 103 research articles published in variou s research databases. These articles have been selected based on specific criteria to find the most relevant findings in the field of AD detection. The review was carried out based on deep learning techniques such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transfe r Learning (TL). To propose accurate methods for the detection, segmentation, and severity grading of AD, the radiological features need to be examined in greater depth. This review attempts to analyze different deep learning methods applied for AD detection using ne...
Source: Neuroinformatics - March 8, 2023 Category: Neuroscience Source Type: research
Multimodal 3D Mouse Brain Atlas Framework with the Skull-Derived Coordinate System
In this study, we have developed a bidirectional multimodal atlas framework that includes brain templates based on both imaging modalities, region delineations from the Allen ’s Common Coordinate Framework, and a skull-derived stereotaxic coordinate system. The framework also provides algorithms for bidirectional transformation of results obtained using either MR or LSFM (iDISCO cleared) mouse brain imaging while the coordinate system enables users to easily assign in vivo coordinates across the different brain templates. (Source: Neuroinformatics)
Source: Neuroinformatics - February 21, 2023 Category: Neuroscience Source Type: research
On the Long-term Archiving of Research Data
AbstractAccessing research data at any time is what FAIR (Findable Accessible Interoperable Reusable) data sharing aims to achieve at scale. Yet, we argue that it is not sustainable to keep accumulating and maintaining all datasets for rapid access, considering the monetary and ecological cost of maintaining repositories. Here, we address the issue of cold data storage: when to dispose of data for offline storage, how can this be done while maintaining FAIR principles and who should be responsible for cold archiving and long-term preservation. (Source: Neuroinformatics)
Source: Neuroinformatics - February 1, 2023 Category: Neuroscience Source Type: research
Correction to: Multi-Subject Analysis for Brain Developmental Patterns Discovery via Tensor Decomposition of MEG Data
(Source: Neuroinformatics)
Source: Neuroinformatics - January 17, 2023 Category: Neuroscience Source Type: research
NiftyPAD - Novel Python Package for Quantitative Analysis of Dynamic PET Data
AbstractCurrent PET datasets are becoming larger, thereby increasing the demand for fast and reproducible processing pipelines. This paper presents a freely available, open source, Python-based software package called NiftyPAD, for versatile analyses of static, full or dual-time window dynamic brain PET data. The key novelties of NiftyPAD are the analyses of dual-time window scans with reference input processing, pharmacokinetic modelling with shortened PET acquisitions through the incorporation of arterial spin labelling (ASL)-derived relative perfusion measures, as well as optional PET data-based motion correction. Resul...
Source: Neuroinformatics - January 9, 2023 Category: Neuroscience Source Type: research
IABC: A Toolbox for Intelligent Analysis of Brain Connectivity
AbstractBrain functional networks and connectivity have played an important role in exploring brain function for understanding the brain and disclosing the mechanisms of brain disorders. Independent component analysis (ICA) is one of the most widely applied data-driven methods to extract brain functional networks/connectivity. However, it is hard to guarantee the reliability of networks/connectivity due to the randomness of component order and the difficulty in selecting an optimal component number in ICA. To facilitate the analysis of brain functional networks and connectivity using ICA, we developed a MATLAB toolbox call...
Source: Neuroinformatics - January 7, 2023 Category: Neuroscience Source Type: research
Correction to: Deconvolution of the Functional Ultrasound Response in the Mouse Visual Pathway Using Block-Term Decomposition
(Source: Neuroinformatics)
Source: Neuroinformatics - December 26, 2022 Category: Neuroscience Source Type: research
