Abstract #3735

Automated reference tissue normalization of prostate T2-weighted MRI on a large, multicenter dataset

Kaia Ingerdatter Sørland¹, Mohammed R. S. Sunoqrot¹, Pål Erik Goa^2,3, Elise Sandsmark³, Sverre Langørgen³, Helena Bertilsson^4,5, Gigin Lin⁶, Tone F. Bathen^1,3, and Mattijs Elschot^1,3

¹Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway, ²Department of Physics, Norwegian University of Science and Technology, Trondheim, Norway, ³Department of Radiology and Nuclear Medicine, St. Olavs University Hospital, Trondheim, Norway, ⁴Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway, ⁵Department of Urology, St. Olavs University Hospital, Trondheim, Norway, ⁶Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Institute for Radiological Research, Chang Gung University, Taoyuan, Taiwan

Scanner-dependent variations induce non-standard signal intensities (SI) in T2-weighted (T2W) MR images. These variations make computer aided diagnosis of prostate cancer based on T2W images challenging, and SI normalization is necessary. Autoref is a normalization method for axial T2W prostate MRI based on two reference tissues of high and low intensity. The aim of this work was to evaluate Autoref’s performance on a large dataset, and to investigate its performance for various reference tissues. Femoral head and fat were proven to be stable reference tissues, significantly reducing inter-scan variation.

How to access this content:

For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.

After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.

After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.

Click here for more information on becoming a member.