Automated Classification of Body MRI Sequence Type Using Convolutional Neural Networks

Multi-parametric MRI of the body is routinely acquired for the identification of abnormalities and diagnosis of diseases. However, a standard naming convention for the MRI protocols and associated sequences does not exist due to wide variations in imaging practice at institutions and myriad MRI scanners from various manufacturers being used for imaging. The intensity distributions of MRI sequences differ widely as a result, and there also exists information conflicts related to the sequence type in the DICOM headers. At present, …

acquired automated classification convention convolutional neural networks cs.cv diagnosis diseases eess.iv identification imaging mri networks neural networks parametric practice standard type