Package gov.nih.mipav.view.renderer.WildMagic.Knees
package gov.nih.mipav.view.renderer.WildMagic.Knees
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ClassesClassDescriptionThis code is used to create VOI from Alexnet generated energy maps.The class is the driver for the AAM classification.The class is the driver for the AAM classification.The class is the driver for the AAM classification.For knees project, reconstruct the 3D surface from VOIs.This class converts the original knees MRI images into isotropic images. 1) Convert the VOIs into binary image masks. 2) Convert the original images into isotropic images 3) Convert the isotropic images from sagittal to axial; sagittal to coronal. 4) Along each orietation, generate the CED image in addition to MRI. 5) Save all the images (isotropic axial, sagittal, coronal images with corresponding binary masks).This class convert the 3D images to 2D slices based png files for single MRI GRE image alone.Test case: generate the femur VOI contours from Alexnet generated deep learning energy maps. -------------------------------------------------------- No longer need it.This class generates the knees VOI contours from the deep learning HED MRI and CED energy maps.Generate the 2D 32x32 patches for both training and testing cased. 1) AAM generates the initial contours. 2) Alone each normal line of the contour point, extract 32x32 patches for both training and testing cases -------------------------------------------------------- No longer need it.Patella segmentation for Netherland data.The class is the driver for the AAM classification.This class generates the knees VOI contours from the deep learning (HNN) MRI and CED energy maps.This class generates the knees VOI contours from the deep learning HED MRI maps.The class prepare the evalution masks for segmentation result and ground truth label.This class converts the original knees MRI images into isotropic images. 1) Convert the VOIs into binary image masks. 2) Transform the binary mask images to original image resolution. 3) Then, save the binary mask into .nii file format for comparison.The class converts the 2D-volumetric approach axial, sagittal and coronal MRI and CED png slices (or MRI png slices alone) into a file list.This class converts the original knees MRI images into isotropic images. 1) Convert the VOIs into binary image masks. 2) Convert the original images into isotropic images 3) Convert the isotropic images from sagittal to axial; sagittal to coronal. 4) Along each orietation, generate the CED image in addition to MRI. 5) Save all the images (isotropic axial, sagittal, coronal images with corresponding binary masks).