Results 1 to 10 of about 758,831 (346)

Scale-space for empty catheter segmentation in PCI fluoroscopic images [PDF]

International Journal of Computer Assisted Radiology and Surgery, 2017
In this article, we present a method for empty guiding catheter segmentation in fluoroscopic X-ray images. The guiding catheter, being a commonly visible landmark, its segmentation is an important and a difficult brick for Percutaneous Coronary Intervention (PCI) procedure modeling.In number of clinical situations, the catheter is empty and appears as ...
Jean Cousty, Régis Vaillant, Ketan Bacchuwar, Ketan Bacchuwar, Laurent Najman   +4 more
semanticscholar   +7 more sources

Scale-Space Autoencoders for Unsupervised Anomaly Segmentation in Brain MRI [PDF]

International Conference on Medical Image Computing and Computer-Assisted Intervention, 2020
Brain pathologies can vary greatly in size and shape, ranging from few pixels (i.e. MS lesions) to large, space-occupying tumors. Recently proposed Autoencoder-based methods for unsupervised anomaly segmentation in brain MRI have shown promising performance, but face difficulties in modeling distributions with high fidelity, which is crucial for ...
Benedikt Wiestler, Nassir Navab, Christoph Baur, Shadi Albarqouni   +3 more
semanticscholar   +6 more sources

Colour Morphological Scale-Spaces for Image Segmentation [PDF]

Procedings of the British Machine Vision Conference 2005, 2005
Morphological scale-spaces have become an important tool for analysing greyscale images. However, their extension to colour images has proven elusive until recently. In this paper an original evaluation of two recently proposed colour sieves is presented, both algorithmically and in terms of their computational and segmentation performance.
David Gimenez, Adrian N. Evans
openaire   +3 more sources

Image segmentation through the scale-space random walker [PDF]

, 2021
This thesis proposes an extension to the Random Walks assisted segmentation algorithm that allows it to operate on a scale-space. Scale-space is a multi-resolution signal analysis method that retains all of the structures in an image through progressive blurring with a Gaussian kernel.
Richard Rzeszutek
  +6 more sources

Scale Space Operators on Hierarchies of Segmentations [PDF]

, 2013
A hierarchy of segmentations(partitions) is a multiscale set representation of the image. This paper introduces a new set of scale space operators or transformations on the space of hierarchies of partitions. An ordering of hierarchies is proposed which is endowed by an ω-ordering based on a global energy over the classes of the hierarchy.
Kiran, Bangalore Ravi, Serra, Jean
openaire   +4 more sources

False positive reduction in CADe using diffusing scale space [PDF]

, 2014
Segmentation is typically the first step in computer-aided-detection (CADe). The second step is false positive reduction which usually involves computing a large number of features with thresholds set by training over excessive data set.
Brady, Michael, Highnam, Ralph, Janan, Faraz   +2 more
core   +1 more source

Identifying Components in 3D Density Maps of Protein Nanomachines by Multi-scale Segmentation [PDF]

, 2009
Segmentation of density maps obtained using cryo-electron microscopy (cryo-EM) is a challenging task, and is typically accomplished by time-intensive interactive methods.
Chiu, Wah, Gossard, David C., Pintilie, Grigore Dimitrie, Zhang, Junjie   +3 more
core   +1 more source

Combining Contrast Invariant L1 Data Fidelities with Nonlinear Spectral Image Decomposition [PDF]

, 2017
This paper focuses on multi-scale approaches for variational methods and corresponding gradient flows. Recently, for convex regularization functionals such as total variation, new theory and algorithms for nonlinear eigenvalue problems via nonlinear ...
A Chambolle, A Haddad, A Hoover, C Brune, C Wu, C Zach, D Strong, G Bellettini, G Gilboa, G Gilboa, G Gilboa, J Yuan, JF Aujol, L Zeune, M Burger, M Burger, M Nikolova, S Osher, TF Chan, V Caselles, V Duval, W Yin, Y Dong   +22 more
core   +3 more sources

DroTrack: High-speed Drone-based Object Tracking Under Uncertainty

, 2020
We present DroTrack, a high-speed visual single-object tracking framework for drone-captured video sequences. Most of the existing object tracking methods are designed to tackle well-known challenges, such as occlusion and cluttered backgrounds.
Hamdi, Ali, Kim, Du Yong, Salim, Flora
core   +1 more source

Automated Visual Fin Identification of Individual Great White Sharks [PDF]

, 2016
This paper discusses the automated visual identification of individual great white sharks from dorsal fin imagery. We propose a computer vision photo ID system and report recognition results over a database of thousands of unconstrained fin images.
Burghardt, Tilo, Hughes, Benjamin
core   +2 more sources