1 citations · 2 across the 5 of their papers we have counts for
7 papers · 1 filter
Unified Attentional Generative Adversarial Network for Brain Tumor Segmentation From Multimodal Unpaired Images
Wenguang Yuan, Jia Wei, Jiabing Wang +2
In medical applications, the same anatomical structures may be observed in multiple modalities despite the different image characteristics. Currently, most deep models for multimod…
Image Segmentation with Pseudo-marginal MCMC Sampling and Nonparametric Shape Priors
Ertunc Erdil, Sinan Yildirim, Tolga Tasdizen +1
In this paper, we propose an efficient pseudo-marginal Markov chain Monte Carlo (MCMC) sampling approach to draw samples from posterior shape distributions for image segmentation.…
Appearance invariance in convolutional networks with neighborhood similarity
Tolga Tasdizen, Mehdi Sajjadi, Mehran Javanmardi +1
We present a neighborhood similarity layer (NSL) which induces appearance invariance in a network when used in conjunction with convolutional layers. We are motivated by the observ…
Disjunctive Normal Level Set: An Efficient Parametric Implicit Method
Fitsum Mesadi, Mujdat Cetin, Tolga Tasdizen
Level set methods are widely used for image segmentation because of their capability to handle topological changes. In this paper, we propose a novel parametric level set method ca…
Convex Decomposition And Efficient Shape Representation Using Deformable Convex Polytopes
Fitsum Mesadi, Tolga Tasdizen
Decomposition of shapes into (approximate) convex parts is essential for applications such as part-based shape representation, shape matching, and collision detection. In this pape…
Regularization With Stochastic Transformations and Perturbations for Deep Semi-Supervised Learning
Mehdi Sajjadi, Mehran Javanmardi, Tolga Tasdizen
Effective convolutional neural networks are trained on large sets of labeled data. However, creating large labeled datasets is a very costly and time-consuming task. Semi-supervise…