BrainVoyager 21.4 神經影像數據管理和分析軟體
- BrainVoyager 21.4 神經影像數據管理和分析軟體
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類別研究分析軟體
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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。
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價格
BrainVoyager QX
核磁共振圖片視覺化分析軟體
全面而強大的神經影像工具具有許多令人興奮的功能，
• 極其快速且高度優化的2D和3D分析和可視化程序
• 基於體積和皮質的假設驅動的統計數據分析（即GLM）包括連接和隨機效應分析
• 隨機效應ANCOVA分析先進的多因素設計和與外部（即行為）變量的相關性
• 使用假髮現率（FDR）方法進行動態統計閾值處理以校正多重比較
• 用於校正多重比較的群集大小閾值（插件）
• 多主題感興趣體積（VOI）和表面感興趣（POI）分析
• 使用獨立成分分析（ICA）進行基於體積和皮質的數據驅動分析
• 用於自動腦分割，表面重建，皮質膨脹和扁平化的高級方法
• 基於皮質的受試者間對齊基於個體大腦的旋轉/溝模式超越Talairach空間
• 擴散張量成像（DTI）數據的分析（在製品）包括結合可視化與結構和功能MRI
• 創建（“播種”）和EEG / MEG多偶極子模型的可視化結合強大的BESA 5.0程序
• 將體積和表面渲染與強大的工具集成，以創建高質量的數字和電影
• 神經導航模塊作為TMS Neuronavigator系統的一部分。
• 多處理器支持和具有文檔格式的開放式架構
• 跨平台腳本支持允許以批處理模式分析來自許多主題的數據
• 跨平台C ++插件支持，可以擴展BrainVoyager QX的功能
• Windows版本（v2.x）將支持基於COM的接口，可以使用所有主要計算機語言（即C / C ++，VB，Java）以及MATLAB訪問這些接口
• 唯一完整的解決方案，可在所有主要計算機平台上運行，包括Windows，Linux / Unix和Mac OS X.
• BrainVoyager QX提供了一個集成在單個產品中的綜合跨平台解決方案。該軟件允許在平台之間輕鬆交換數據，處理透明的潛在字節順序差異（“big endian”與“little endian”）。在一個平台上分析的數據（例如Windows）可以移動到另一個平台 - 例如Mac OS X - 並進一步處理而沒有問題
請注意，BrainVoyager QX需要HASP跨平台加密狗用於單台計算機或網絡加密狗提供“浮動”許可證。HASP許可證系統允許您在Windows，Linux和Mac OS X上使用該程序。購買BrainVoyager QX（或BrainVoyager 2000）後，您將收到所有這些平台的可執行文件。如果您想在Unix上使用BrainVoyager QX（即Sun Solaris），請發送電子郵件給我們，我們將向您發送有關BrainVoyager QX for Unix平台可用性的更多信息。
產品安裝硬體規格
Windows 10 或 Windows (64位)操作系統
至少4 GB，建議至少8 GB
BrainVoyager
核磁共振圖片視覺化分析軟體
全面而強大的神經影像工具有許多令人興奮的功能，
• 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.
ACBC 自適選擇聯合分析軟體
ACBC是一種新的偏好建模方法，利用了CBC(Choice-Based Conjoint）和ACA（Adaptive Conjoint Analysis）的最佳方面。 自適應選擇面試是一種互動體驗，根據每個人的偏好和意見進行定制。CBC/ACA是Teechart旗下久負盛名的聯合分析（Conjoint Analysis）軟體，聯合分析也稱為結合分析。CBC/ACA可以獲得水平的效用值，屬性的相對重要程度，市場細分，預測市場偏好份額等分析結果。
CART® 資料挖掘分析軟體
CART® 是Salford Systems的旗艦數據挖掘軟件，該軟件是一款功能強大、易操作的決策樹，能自動篩選複雜的數據。從技術上講，CART建模引擎基於1984年由斯坦福大學和加州大學伯克利分校的四位世界知名統計學家引入的具有里程碑意義的數學理論。CART建模引擎是SPM的分類和回歸樹實現，是唯一體現原始專有代碼的決策樹軟件。
MODDE 12 實驗計劃與分析軟體
MODDE引導您完成您的試驗設計（DOE）設計的設置和支持你在隨後的數據分析。對於醫藥和其他關鍵應用領域，因為任何人在產品開發都知道，把事情從一開始就是一個挑戰。特別是有這麼多的參數來考慮。對於像醫藥產業領域的成果是至關重要的，競爭是激烈的，你需要的工具，你可以肯定將讓你在市場上的時間。
