ADNI挑选有意义的数据进行下载【2】

最新推荐文章于 2025-06-13 09:00:13 发布

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最新推荐文章于 2025-06-13 09:00:13 发布 · 4.7k 阅读

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#ADNI #Alzheimer #image process #老年痴呆 #影像处理

这篇博客介绍了ADNI数据集中MRI和FDG-PET图像的预处理步骤，包括梯度偏差校正、B1非均匀性校正和N3算法的应用。还详细说明了如何根据论文要求在ADNI数据集中搜索符合条件的MRI和PET图像，以及如何下载和组织这些数据。

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ADNI数据集本身提供处理过的图片

有一篇论文“Non-White Matter Tissue Extraction and Deep Convolutional Neural Network for Alzheimer’s Disease Detection
”中涉及到的预处理的数据如下：
“We use the FDG-PET and MRI data downloaded from ADNI1 dataset with each pair of FDG-PET and MRI for same subject and captured at the same time. The MRI and PET images have undergone several preprocessed steps of research groups belonged to the ADNI.”
In detail, the MRI images are pre-processed by steps: gradwarp, B1 non-uniformity and N3. Gradwarp means correction of image geometry distortion due to gradient model, B1 non-uniformity is a correction procedure that uses B1 calibration scans to correct image intensity nonuniformity. Finally, a N3 histogram peak sharpening algorithm was applied to reduce intensity non-uniformity of images. （其中，对MRI图像进行预处理的步骤有:梯度偏差、B1非均匀性和N3。梯度偏差是指梯度模型引起的图像几何畸变的校正，B1非均匀性是利用B1校正扫描对图像强度非均匀性进行校正的一种校正方法。最后，采用N3直方图峰值锐化算法来降低图像的强度不均匀性）
For the FDG-P