Nejat Yigit Can

I am a Ph.D. student at the University of Southern California in the Department of Electrical and Computer Engineering. Previously, I was at the University of Rochester and the Martinos Center.

Current research: image reconstruction with undersampled data, machine learning. Past research: Brillouin microscopy, osteoarthritis mechanobiology.

Outside of research, I am into skiing, filmmaking, photography, hiking, and cycling!

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We demonstrate combination of MaxGIRF and STCR to achieve concomitant field corrected dynamic MRI. This is particularly valuable for large-FOV and table-shifted imaging at low field strengths such as 0.55 T.

Physics-based unsupervised deep learning for diffusion tensor estimation is a high fidelity and feasible alternative method to the LLSQ estimation. Estimating the diffusion tensor with our method is 17.5 times faster than the conventional LLSQ method.

Articular chondrocytes in severe PT-OA are more fragile from mechanical impacts than chondrocytes in healthy or mild PT-OA. Thus, preserving physiologic joint-loads on injured joints will reduce chondrocyte death postinjury and may delay PT-OA progression.

Higher weight bearing gait pattern-induced by ACL injury presumably leads to abnormal loading environment and exacerbates cell mechano-vulnerability, which in turn may result in cartilage degradation in the form of OA.