BrainVoyager 22.0 核磁共振圖片視覺化分析軟體-資安軟體/研究分析軟體/心理學軟體/新永資訊有限公司

BrainVoyager 22.0 神經影像數據管理和分析軟體

BrainVoyager 22.0 神經影像數據管理和分析軟體

  • BrainVoyager 22.0 神經影像數據管理和分析軟體
  • 編號
  • 類別
    研究分析軟體
  • 介紹
    BrainVoyager 是一種高度優化和用戶友好的軟件包,用於分析和可視化功能和結構磁共振成像數據集。該程序可在所有主要計算機平台上運行,包括Windows(XP / 7/8 / 8.1),Linux(例如RedHat,SUSE)和Mac OS X(10.8或更高版本)。結合最佳的跨平台技術,BrainVoyager QX在所有支持的平台上提供原生且響應迅速的用戶界面。
  • 價格

BrainVoyager 22.0 neuroimaging data management and analysis software

Our flagship product BrainVoyager is a powerful neuroimaging software package for data management and data analysis. It started as a tool for the analysis of anatomical and functional MRI data sets but has evolved over the years into a multi-modal analysis tool for fMRI, DTI, EEG and MEG data. The software is highly optimized and user friendly running on all major computer platforms; BrainVoyager is a 64 bit program supporting analyses of large data sets that need more than 3 GB of RAM. In order to obtain maximum speed on each platform, BrainVoyager has been programmed in C++ with optimized and highly efficient statistical, numerical, and image processing routines. It supports on all platforms fast parallelized basic math routines using the Intel Math Kernel Library (MKL). The software also exploits modern multi-core, multi-processor hardware for the most demanding computational routines. Multiple parallel processing pipelines of modern graphic cards (GPU's) are used for real-time volume rendering, data filtering and sinc interpolation. The surface rendering environment ("surface module") has been implemented using OpenGL. The interactive graphical user interface (GUI) has been built using the award-winning cross-platform Qt C++/QML toolkit from Digia (formerly Nokia and Trolltech). Using cross-platform C++/QML code for all aspects of the program, BrainVoyager provides a native and responsive user interface and powerful computational routines on all supported platforms.
The comprehensive and powerful neuroimaging tool comes with many exciting features, such as:
A modern graphical user interface.
New data management capabilities providing a hierarchical view on your data.
New workflow tools allowing to specify, execute and document complete analyses across all subjects of an experiment.
Very fast and highly optimized 2D and 3D analysis and visualization routines.
A comprehensive set of efficient pre-processing tools, including motion correction, high-pass filtering and slice scan time correction.
Fast and precise coregistration of functional and anatomical data sets including boundary-based registration.
Automatic MNI and Talairach brain normalization tools.
Volume and cortex-based hypothesis-driven statistical data analysis using the General Linear Model (GLM).
Random-effects ANCOVA analysis for advanced multi-factorial designs and correlation with external (e.g. behavioral) variables.
Nonparametric Permutation Inference for Multi-Subject Designs including threshold-free cluster enhancement.
Cluster-size thresholding for correction of multiple comparisons for volume and surface maps.
Multi-voxel pattern analysis (MVPA) tools, including support vector machines (SVMs) and recursive feature elimination (RFE).
Distributed source EEG and MEG cortical imaging and analysis of EEG-fMRI coupling for simultaneous measurements with artifact correction.
Analysis of Diffusion-Weighted Imaging (DWI) including combined visualization of tracked fiber bundles with structural and functional MRI.
Dynamic statistical thresholding using the False Discovery Rate (FDR) approach for correction of multiple comparisons.
Retinotopic mapping analysis using population receptive field (pRF) estimation as well as classical phase-encoded analysis.
Multi-subject Volume-of-Interest (VOI) and surface Patch-of-Interest (POI) analysis.
Volume and cortex-based data-driven analysis using Independent Component Analysis (ICA) performing single run as well as group analyses.
Cortical thickness analysis for advanced morphometry.
Automatic coregistration of functional and diffusion-weighted data with high-resolution 3D anatomical data sets
Advanced methods for automatic brain segmentation, surface reconstruction, cortex inflation and flattening.
Powerful manual segmentation tools.
Cortex-based inter-subject alignment based on gyral / sulcal pattern of individual brains going beyond standard volumetric normalization approaches such as Talairach transformation.
Creation ("seeding") and visualization of EEG / MEG multiple dipole models in combination with the powerful BESA program.
Integration of volume and surface rendering with powerful tools for the creation of high-quality figures and movies.
Advanced visualizations of anatomical and functional data sets with real-time GPU-based volume rendering.
A real-time neuronavigation module as part of the TMS Neuronavigator system.
Multi-core and multi-processor support and an open architecture with documented file formats.
Cross-platform scripting support allowing to analyze the data from many subjects in batch mode.
Cross-platform C++ plugin support which makes it possible to extent the functionality of BrainVoyager.
The Windows version supports COM-based interfaces, which can be accessed with all major computer languages (e.g. C/C++, VB, Java) as well as from MATLAB.
The macOS version supports AppleScript scripting allowing to automate BrainVoyager from outside the program and to integrate it in scripted workflows with other programs.
Since BrainVoyager 20, it is possible to develop scripts and plugins using the Python language.
Optimized native executables for all major computer platforms including Windows, Linux and macOS.
BrainVoyager provides a comprehensive cross-platform solution embodied in a single product. The software allows easy exchange of data between platforms handling transparently potential byte order differences ("big endian" vs "little endian"). Data analyzed on one platform - for example Windows - can be moved to another platform - for example macOS - and processed further without any problem.
Note that with BrainVoyager 20.0, the name and version numbering of BrainVoyager has been changed. The "QX" part from previous version names has been dropped since it is no longer necessary to stress the cross-platform nature of BrainVoyager. Furthermore, version numbers now follow a yearly release cycle starting with BrainVoyager 1.0 (Windows version) released in June 1996. In order to be compatible with previous naming and licensing terms, BrainVoyager 20.X is internally also coded as BrainVoyager QX 3.X.

BrainVoyager 22.0 Now Available With Major New Features

We are happy to announce the availability of BrainVoyager 22.0, which is a major release introducing important new features. The two most outstanding new features are BV Notebooks for reproducible data analysis and an advanced cortex segmentation tool that is based on a deep neural network (DNN) with an advanced "Tiramisu" architecture. These as well as other new features, enhancements and bug fixes are described in the release notes and the updated 22.0 User's Guide.
The DNN segmentation tool has been developed for high-resolution sub-millimeter data to segment grey matter with very high accuracy both along the inner (white-grey) and outer (pial) boundary. The high-quality segmentations are especially suited for cortical thickness measurements and mesoscopic (laminar and columnar) fMRI analyses.
The introduced BV Notebooks offer (script) programmers a means to write Python code to document performed analysis steps. BV Notebooks are inspired by Jupyter notebooks but they offer many BrainVoyager-specific features. Probably the most unique feature is that they support reproducible analyses also for users that do not (want to) program by converting essential GUI actions into corresponding code. Both manual as well as auto-generated code can be easily enriched with images, animations, rendered Markdown text as well as embedded BrainVoyager viewers enabling any BrainVoyager user to create rich documents. 

系統需求

OS
當前版本可在Windows(7/8/10),Linux(例如Ubuntu,SUSE,Fedora)和macOS(10.10或更高版本)上運行。

 

BrainVoyager 22.0 神經影像數據管理和分析軟體

我們的旗艦產品BrainVoyager是用於數據管理和數據分析的功能強大的神經影像軟件包。
它起初是用於分析解剖和功能性MRI數據集的工具,但多年來已發展成為用於fMRI,DTI,EEG和MEG數據的多模式分析工具。該軟件經過高度優化,並且在所有主要計算機平台上都易於操作。
BrainVoyager是一個64位程序,支持對需要3 GB以上RAM的大型數據集進行分析。
為了在每個平台上獲得最大速度,BrainVoyager已經用C ++進行了編程,具有優化和高效的統計,
數值和圖像處理例程。它在所有平台上都支持使用英特爾數學內核庫(MKL)。
該軟件還利用現代的多核,多處理器硬件來滿足最苛刻的計算例程。
現代圖形卡(GPU)的多個並行處理管道用於實時體積渲染,數據過濾和Sinc插值。
表面渲染環境(“表面模塊”)已使用OpenGL實現。
交互式圖形用戶界面
(GUI)是使用Digia(曾是諾基亞和Trolltech)屢獲殊榮的跨平台Qt C ++ / QML工具包構建的。
在程序的所有方面使用跨平台的C ++ / QML代碼,
BrainVoyager在所有受支持的平台上提供了本機且響應迅速的用戶界面以及強大的計算例程。

全面而強大的神經影像工具具有許多令人興奮的功能,例如:
現代化的圖形用戶界面。 新的數據管理功能可提供數據的分層視圖。
新的工作流程工具可用於指定,執行和記錄整個實驗所有主題的完整分析。
快速,高度優化的2D和3D分析和可視化例程。
一整套有效的預處理工具,包括運動校正,高通濾波和切片掃描時間校正。
功能和解剖數據集的快速,精確整合,包括基於邊界的配準。
自動MNI和Talairach腦歸一化工具。
使用通用線性模型(GLM)進行基於體積和皮質的假設驅動的統計數據分析。
用於高級多因素設計並與外部(例如行為)變量相關的隨機效應ANCOVA分析。
多主題設計的非參數置換推斷,包括無閾值聚類增強。
群集大小閾值,用於校正體積和表面貼圖的多個比較。
多體素模式分析(MVPA)工具,包括支持向量機(SVM)和遞歸特徵消除(RFE)。
分佈式源EEG和MEG皮質成像以及EEG-fMRI耦合分析,可同時進行偽影校正測量。
彌散加權成像(DWI)分析,包括跟踪的纖維束與結構和功能MRI的組合可視化。
使用錯誤發現率(FDR)方法進行動態統計閾值校正多個比較。
使用人口感受野(pRF)估計以及經典的相位編碼分析進行視網膜圖像定位分析。
多主題興趣量(VOI)和表面興趣補丁(POI)分析。
使用獨立成分分析(ICA)進行單次運行和組分析的基於體積和皮質的數據驅動分析。
用於高級形態測量的皮質厚度分析。
具有高分辨率3D解剖數據集的功能和擴散加權數據的自動配準
自動進行腦部分割,表面重建,皮質膨脹和展平的先進方法。
強大的手動細分工具。
基於皮質的個體間對準基於個體大腦的迴旋/溝紋模式,超越了諸如Talairach變換之類的標準體積歸一化方法。
結合強大的BESA程序,創建(“播種”)並可視化EEG / MEG多個偶極子模型。
將體積和表面渲染與功能強大的工具集成在一起,以創建高質量的人物和電影。
借助基於GPU的實時體繪製,對解剖學和功能數據集進行高級可視化。
作為TMS Neuronavigator系統一部分的實時神經導航模塊。
多核和多處理器支持以及具有記錄的文件格式的開放式體系結構。
跨平台腳本支持支持以批處理模式分析來自多個主題的數據。
跨平台的C ++插件支持使擴展BrainVoyager的功能成為可能。
Windows版本支持基於COM的界面,可以使用所有主要的計算機語言(例如C / C ++,VB,Java)以及從MATLAB進行訪問。
macOS版本支持AppleScript腳本,從而可以從程序外部自動執行BrainVoyager,並將其與其他程序集成到腳本工作流程中。
從BrainVoyager 20開始,可以使用Python語言開發腳本和插件。
針對所有主要計算機平台(包括Windows,Linux和macOS)的優化本機可執行文件。

BrainVoyager 22.0現在具有主要的新功能

我們很高興宣布BrainVoyager 22.0的可用性,它是引入重要新功能的主要版本。兩個最傑出的新功能是用於可重複數據分析的BV筆記本電腦和基於具有高級“提拉米蘇”架構的深度神經網絡(DNN)的高級皮質分割工具。這些功能以及其他新功能,增強功能和錯誤修復在發行說明和更新的《 22.0用戶指南》中都有介紹。
DNN分割工具已經開發出來,用於高分辨率的亞毫米波數據,可以沿內部(白灰色)和外部(螺旋)邊界以非常高的精度分割灰質。高質量的分割尤其適用於皮層厚度測量和介觀(層狀和柱狀)fMRI分析。
引入的BV筆記本為(腳本)程序員提供了一種編寫Python代碼來記錄執行的分析步驟的方法。BV筆記本電腦受到Jupyter筆記本電腦的啟發,但是它們提供了BrainVoyager的許多特定功能。可能最獨特的功能是,它們還為不(不想)編程的用戶提供了可重複的分析,方法是將基本的GUI操作轉換為相應的代碼。手動以及自動生成的代碼都可以輕鬆地添加圖像,動畫,渲染的Markdown文本以及嵌入式BrainVoyager查看器,從而使任何BrainVoyager用戶都可以創建豐富的文檔。

 

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