Hi, I would like to know if there are any studies related to the classification of artifacts (also presence / absence) of the knee dataset.
Furthermore, I’d like to know where to find the MRI information for each slices (t1-weighted / t2-weighted, gradient, etc.) of the knee dataset. In the “ismrmrd_header” I find only magnet informations and slices thickness.
Thank you so much.
Hello @SyMon_92, welcome to fastMRI!
I don’t know of studies related to classification of artifacts - are you referring to standard imaging artifacts or deep learning reconstruction artifacts? We discuss deep learning reconstruction artifacts in our recent paper reporting the results of the 2020 fastMRI challenge:
The main way I look at the sequence is usually with
hf.attrs['acquisition']
Which, for example, might output CORPD_FS for a coronal proton density scan with fat saturation.
Hi @mmuckley, thank you very much for the quick reply!
Yes, I’m referring to standard imaging artifacts (e.g. metal prosthesis, motion, etc.).
Thanks for the hf.attrs[‘acquisition’] command, it works great.
For the raw data of knee dataset, is there any command that for each slice, shows the specific position in the coronal axis? For example, I would need to select all MRIs with the same perspective for each scan.
Thank you
I don’t know of any studies of artifacts in the fastMRI data, but there could be something in the literature.
Hmm, I’m not sure I have a solution for the positioning. You could try to inquire the people at NYU for that information.
fastmri@med.nyu.edu