Medical Image Segmentation and Applications (MISA) LAB task.
Functions Used in two codes::
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show_slice(img, slice_no):
Inputs: Name of the Image Array, img=name.get_fdata() Slice number you want to knoe,Slice no = 24 output: Plot Image.
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gmm(x, mean, cov):
Inputs: x (numpy.ndarray): nxd dimentional array. where n= number of samples d= dimention mean (numpy.ndarray): d-dimentional mean value. cov (numpy.ndarray): dxd dimentional covariance matrix.
output: (numpy.ndarray): Gaussian mixture for every point in feature space.
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dice_similarity(Seg_img, GT_img,state):
Inputs: Seg_img (numpy.ndarray): Segmented Image. GT_img (numpy.ndarray): Ground Truth Image. State: "nifti" if the images are nifti file "arr" if the images are an ndarray
output: Dice Similarity Coefficient: dice_CSF, dice_GM, dice_WM.
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Dice_and_Visualization_of_one_slice(Seg_img, GT_img,state,number_of_slice): """Example Use: Dice_and_Visualization_of_one_slice(Seg,Label_img,"arr",30)"""
Inputs: Seg_img (numpy.ndarray): Segmented Image. GT_img (numpy.ndarray): Ground Truth Image. State: "nifti" if the images are nifti file "arr" if the images are an ndarray output: Dice Similarity Coefficient: dice_CSF, dice_GM, dice_WM. Ploting image