I have imported a DICOM file of a shoulder MRI scan, however, each view appears distorted. When attempting to load the axial view image set, the axial view scan is clear, and the other views are blurry. When attempting to load the coronal view image set, the axial view is blurry, and the other views are partially clear, with a ripple appearance along the edges of the bones. I have included images of each loaded file in this post to show how the views appear. Is there a method to viewing these images clearly?
This protocol of acquiring 3 sparse volumes (instead of one high-resolution volume) is very common for musculoskeletal MRI, probably because it saves acquisition time and it is fine for humans to read such images. Unfortunately, these images are not optimal for 3D analysis. See this topic for more details:
Thank you for the information. My knowledge of using 3D Slicer is limited as I am learning information, and I appreciate your time and assistance. If using data with isotropic spacing for better resolution images is the better way to analyze 3D volumes, are there methods for obtaining this type of data without understanding computer programming?
Would anyone be able to explain or provide a source that explains how to complete the crop volume module method that was mentioned?
To get a more isotropic dataset this ideally needs to be done on the MRI machine by using thinner slice thicknesses when performing the scan, however, I think that this would result in very long scan times which is why MRI often uses thick slices.
You can use the crop volume module to make the voxels isotropic. Go to the crop volume module (under converters). You need to make a Region of Interest (ROI) you can click display ROI and one usually appears. If you want to make the volume smaller you can adjust that shape of the ROI in the slice view windows. You need to click isotropic spacing in the advanced area and b spline interpolation may help slightly to smooth the volume.
Unfortunately you will find that this will not help much. Without a dataset originally acquired with thin slices it is pretty difficult to get good results when segmenting, doing 3D rendering etc. What are you actually trying to do with this volume?