常見問題
常見問題
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Q : What are the system requirements for installing the software?
Q : What are the system requirements for installing the software?
A : Recommended System Requirements:
Operating System: Windows 11 or Windows 10
RAM: A minimum of 8 GB
Storage: At least 8.7 GB of available for MATLAB Runtime (SSD is strongly recommended)
Q : Why is MATLAB Runtime required for installation?
Q : Why is MATLAB Runtime required for installation?
A : This software is developed using the MATLAB programming language and requires the MATLAB Runtime environment to run compiled MATLAB applications.
Please ensure that the version of MATLAB Runtime you install matches the version required by the application.
For more information, visit: https://www.mathworks.com/products/compiler/matlab-runtime.html
Q : An error occurred during the installation process : "The code execution cannot proceed because VCRUNTIME140.dll was not found." ?
Q : An error occurred during the installation process : "The code execution cannot proceed because VCRUNTIME140.dll was not found." ?
A : If you see the error message "The code execution cannot proceed because VCRUNTIME140.dll was not found", it is usually due to a missing Microsoft Visual C++ Redistributable (Microsoft Visual C++可轉散發套件) on your Windows system.
It is recommended to visit the official Microsoft website to download and install the latest version of the Microsoft Visual C++ Redistributable, then try running the program again.
https://learn.microsoft.com/zh-tw/cpp/windows/latest-supported-vc-redist?view=msvc-170
Q : What should I do if only PET images are imported and their poor quality leads to suboptimal spatial normalization?
Q : What should I do if only PET images are imported and their poor quality leads to suboptimal spatial normalization?
A : It is strongly recommended to perform a quality check (QC) on the spatially normalized images.
If spatial normalization is done using PET images alone and the results are poor due to low image quality, consider including MRI images. MRI provides clearer anatomical detail, which can significantly improve the accuracy of spatial normalization.
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