In the paper we propose a new deformable shape model that is based on simplified skeleton graph. Such shape model allows to account for different shape variations and to introduce global constraints like known orientation or scale of the object. We combine the model with low-level image segmentation techniques based on Markov random fields and derive an approximate algorithm for the minimizatio...

Skeletonization is a necessary process in a variety of applications in image processing and object recognition. However, the concept of a skeleton, defined using either the union of centers of maximal discs or the union of points with more than one generating points, was originally formulated in continuous space. When they are applied to situation in discrete space, the resulting skeletons may ...

chondrosarcoma is a mesenchymal tumor composed of tumor cells producing cartilage. it is more common in older age and often affects the axial skeleton. we report a rare case of chondrosarcoma mimicking a sellar and suprasellar mass with parasellar extension. a 40 yr woman presented with decreasing visual acuity and headache. magnetic resonance (mr) image revealed a cystic sellar and suprasellar...

In this paper, we propose a viewpoint-aware action recognition method using skeleton-based features from static images. Our consists of three main steps. First, categorize the viewpoint an input image. Second, extract 2D/3D joints state-of-the-art convolutional neural networks and analyze geometric relationships for computing 2D 3D skeleton features. Finally, perform view-specific classificatio...

In this paper, we present a new and efficient multi-modal 3D-3D vascular registration algorithm, which transforms the 3D-3D registration problem into a multiple 2D-3D vascular registration problem. Along each orthogonal axis, projected 2D image from a segmented binary 3D floating volume is compared with maximum intensity projection (MIP) image of the reference volume. At the preprocessing stage...

His current research interests include computer vision, pattern recognition and special architectures for vision and image processing. He is a student member of IEEE. both in computer science. He is currently a Ph.D. student at Michigan State University. His current research interests include pattern recognition, machine vision and their applications in robotics. India. He has also been a consu...

Conventional networks for object skeleton detection are usually hand-crafted. Although effective, they require intensive priori knowledge to configure representative features objects in different scale granularity.In this paper, we propose adaptive linear span network (AdaLSN), driven by neural architecture search (NAS), automatically and integrate scale-aware detection. AdaLSN is formulated wi...