配置Neruospin/pyprocess的对应参数func_write_voxel_sizes和anat_write_voxel_sizes,原配置内前者为[3,3,3]后者为[1,1,1],很明显功能像那肯定就模糊了,不过我并不清楚这里为何区别功能像和结构像的体素尺寸,有点奇怪,留个问题。不过更改过后尺寸后,分辨率明显改善。 9. Intensity Normalization(whitening) Note...
Python jcreinhold/intensity-normalization Star311 normalize the intensities of various MR image modalities mrifcmneuroimagingstandardizationharmonizationnormalizationzscoreravelintensity-normalizationwhitestripe UpdatedMay 31, 2023 Python mikgroup/sigpy Star308 ...
Intensity normalization brings all images to a common intensity scale, which helps the model focus on structural information rather than variations caused by the imaging process. This step is crucial for improving the model’s sensitivity to the actual pathological features of brain tumors. The ...
Python functions: in /python folder:dwi_simulation.py: Functions for simulating D-MRI signals and evaluation of simulation results of FOD estimation. fod_estimation.py: Functions for the three FOD estimation methods BJS, SHridge and superCSD. fod_HCP_application.py: Functions for HCP data ...
Preprocessing of T1 data consisted of motion correction, skull stripping and intensity normalization using the FreeSurfer image preprocessing pipeline (autorecon2)82. The DTI scan protocol has been described previously73. It consisted of a full-brain multi-shell Stejskal-Tanner pulsed mono-planar gradi...
The pre-processing of images for homogenization included N4 bias field correction34 and intensity normalization with Nyul’s method as adapted by Shah35,36. Enhancement mask definition and thickness quantification The T1w and T1wC images with different slice spacing (1/144 = 1% of the scans...
The histogram normalization was performed twice using the inormalize tool (version 1.5.1 for OS X as part of MINC toolkit) to match the intensity with Dixon in-phase and opposed-phase. The resampled and normalized HUGE images were then used to replace voxels in the Dixon images where the ...
All volumes were preprocessed using an inhouse pipeline (Reiche et al., 2019), which incorporated noise removal, bias field correction, and intensity normalization. The volumes were denoised using 3 × 3 median filtering followed by homomorphic filtering for bias field correction. Intensity ...
To avoid data heterogeneity bias, all MRI data were subjected to imaging normalization (the intensity of the image was scaled to 0–100) and resampled to the same resolution (3 × 3 × 3 mm) before feature extraction. The calculation of texture features was performed using an open...
percentile (float) : Threshold value for the intensity normalization, expressed as percentile threshold (float) : Value of the threshold used to binarize brain masks threshold_pvs (float) : Threshold to binarize PVS clusters after the segmentation threshold_wmh (float) : Threshold to binarize WMH ...