Henry Dieckhaus, Rozanna Meijboom, Serhat Okar, Tianxia Wu, Prasanna Parvathaneni, Yair Mina, Siddharthan Chandran, Adam D Waldman, Daniel S Reich, Govind Nair
OBJECTIVES: Automated whole brain segmentation from magnetic resonance images is of great interest for the development of clinically relevant volumetric markers for various neurological diseases. Although deep learning methods have demonstrated remarkable potential in this area, they may perform poorly in nonoptimal conditions, such as limited training data availability. Manual whole brain segmentation is an incredibly tedious process, so minimizing the data set size required for training segmentation algorithms may be of wide interest...
June 1, 2022: Topics in Magnetic Resonance Imaging: TMRI