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Evaluating the Impact of Intensity Normalization on MR Image Synthesis
Jacob C. Reinhold, Blake E. Dewey, Aaron Carass +1
Image synthesis learns a transformation from the intensity features of an input image to yield a different tissue contrast of the output image. This process has been shown to have…
Unpaired Brain MR-to-CT Synthesis using a Structure-Constrained CycleGAN
Heran Yang, Jian Sun, Aaron Carass +4
The cycleGAN is becoming an influential method in medical image synthesis. However, due to a lack of direct constraints between input and synthetic images, the cycleGAN cannot guar…
A Sparse Non-negative Matrix Factorization Framework for Identifying Functional Units of Tongue Behavior from MRI
Jonghye Woo, Jerry L. Prince, Maureen Stone +8
Muscle coordination patterns of lingual behaviors are synergies generated by deforming local muscle groups in a variety of ways. Functional units are functional muscle groups of lo…
Topology guaranteed segmentation of the human retina from OCT using convolutional neural networks
Yufan He, Aaron Carass, Bruno M. Jedynak +4
Optical coherence tomography (OCT) is a noninvasive imaging modality which can be used to obtain depth images of the retina. The changing layer thicknesses can thus be quantified b…
Cross-modality image synthesis from unpaired data using CycleGAN: Effects of gradient consistency loss and training data size
Yuta Hiasa, Yoshito Otake, Masaki Takao +5
CT is commonly used in orthopedic procedures. MRI is used along with CT to identify muscle structures and diagnose osteonecrosis due to its superior soft tissue contrast. However,…
Self Super-Resolution for Magnetic Resonance Images using Deep Networks
Can Zhao, Aaron Carass, Blake E. Dewey +1
High resolution magnetic resonance~(MR) imaging~(MRI) is desirable in many clinical applications, however, there is a trade-off between resolution, speed of acquisition, and noise.…