In this seminar, I will present an overview of some of my recent work on medical computer vision. The first problem I will talk about is using higher-order tensors in modelling of tree-like structures such as vascular trees in human brain and the heart. We embed the tensor in a 4D space rather than 3D in order to untangle the bifurcating (or even n-furcating) structures/branches in the data in a higher-dimensional space. This led to a highly performing and efficient vessel segmentation framework [1, 2], which is demonstrated on different applications. The second problem I’ll present is on modeling the changes of tumor in brain MRI, which is important for radio-therapy planning and follow-up assessment of the cancer disease. I will present a method for estimation of deformation in brain images, and how it is used to calculate tumor response measures [3,4]. Third, I will show a novel volumetric shape representation based on the screened Poisson partial differential equation and its low dimensional embeddings we call SPEMs , which is applied to a nonrigid shape retrieval problem.
 S. Cetin, G. Unal, “A Higher-order tensor Vessel tractography for segmentation of vascular structures”, to appear, IEEE Transactions on Medical Imaging, 2015.
 S. Cetin, A. Demir, A. Yezzi, M. Degertekin, G. Unal, “Vessel Tractography Using an Intensity Based Tensor Model With Branch Detection”, IEEE Transactions on Medical Imaging, 32(2):348-63; 2013.
 A. Hamamci and G. Unal, “Registration of Brain Tumor Images Using Hyper-Elastic Regularization”, Computational Biomechanics for Medicine: Models, Algorithms and Implementation, Eds. A. Wittek, K. Miller, P.M.F. Nielsen, 2013, pp. 101-114, Springer.
 A. Hamamcı, N. Kucuk, K. Karaman, K. Engin, G. Unal, “Tumor-Cut: Segmentation of Brain Tumors on Contrast-enhanced MR Images for Radiosurgery Applications”, IEEE Transactions on Medical Imaging, Vol.31, No: 3, 790-804, 2012.
 R.A. Guler, S. Tari, G. Unal, “Screened Poisson Hyper-Fields for Shape Coding”, SIAM Journal on Imaging Sciences, Vol. 7 (4), pp. 2558-2590, 2014.