Abstract #1995

Automated multi organ segmentation for 3D fetal body MRI: differences in the normal growth charts for different acquisition parameters

Alena U. Uus¹, Lisa Story^2,3, Megan Hall^3,4,5, Vanessa Kyriakopoulou⁵, Alexia Egloff Collado⁵, Carla Avena Zampieri^1,5, Jacqueline Matthew^1,5, Irina Grigorescu¹, Ayse Ceren Tanritanir⁵, Joseph V. Hajnal^1,5, Jana Hutter^1,5, Mary Rutherford⁵, and Maria Deprez¹

¹Department of Biomedical Engineering, King's College London, London, United Kingdom, ²Academic Women's Health Department, King's College London, London, United Kingdom, ³Fetal Medicine Department, GSTT, London, United Kingdom, ⁴Institute for Women’s and Children’s Health, King's College London, London, United Kingdom, ⁵Centre for the Developing Brain, King's College London, London, United Kingdom

Synopsis

Keywords: Prenatal, SegmentationThis work presents the first deep learning pipeline for segmentation of multiple body organs from motion corrected 3D ssTSE fetal MRI. It is used to compare growth charts of the normal body organ development during 21-37 week GA range for 254 fetal datasets with different acquisition protocols (field strength and TE).

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.