@article {807,
	title = {OpenCLIPER: An OpenCL-Based C++ Framework for Overhead-Reduced Medical Image Processing and Reconstruction on Heterogeneous Devices},
	journal = {IEEE Journal of Biomedical and Health Informatics},
	volume = {23},
	year = {2019},
	month = {July},
	pages = {1702-1709},
	abstract = {<p>Medical image processing is often limited by the computational cost of the involved algorithms. Whereas dedicated computing devices (GPUs in particular) exist and do provide significant efficiency boosts, they have an extra cost of use in terms of housekeeping tasks (device selection and initialization, data streaming, synchronization with the CPU, and others), which may hinder developers from using them. This paper describes an OpenCL-based framework that is capable of handling dedicated computing devices seamlessly and that allows the developer to concentrate on image processing tasks. The framework handles automatically device discovery and initialization, data transfers to and from the device and the file system and kernel loading and compiling. Data structures need to be defined only once independently of the computing device; code is unique, consequently, for every device, including the host CPU. Pinned memory/buffer mapping is used to achieve maximum performance in data transfers. Code fragments included in the paper show how the computing device is almost immediately and effortlessly available to the users algorithms, so they can focus on productive work. Code required for device selection and initialization, data loading and streaming and kernel compilation is minimal and systematic. Algorithms can be thought of as mathematical operators (called processes), with input, output and parameters, and they may be chained one after another easily and efficiently. Also for efficiency, processes can have their initialization work split from their core workload, so process chains and loops do not incur in performance penalties. Algorithm code is independent of the device type targeted.</p>
},
	keywords = {C++, C++ languages, Data structures, GPU, Graphics processing units, Image reconstruction, Informatics, Kernel, Libraries, Medical imaging, OpenCL},
	issn = {2168-2194},
	doi = {10.1109/JBHI.2018.2869421},
	author = {Federico Simmross-Wattenberg and M. Rodr{\'\i}guez-Cayetano and J Royuela-del-Val and E. Mart{\'\i}n-Gonz{\'a}lez and E. Moya-S{\'a}ez and M. Mart{\'\i}n-Fern{\'a}ndez and C. Alberola-L{\'o}pez}
}
@article {796,
	title = {A Second Order Multi-Stencil Fast Marching Method With a Non-Constant Local Cost Model},
	journal = {IEEE Transactions on Image Processing},
	volume = {28},
	year = {2019},
	month = {04/2019},
	pages = {1967{\textendash}1979},
	abstract = {<p>The fast marching method is widely employed in several fields of image processing. Some years ago a multi-stencil version (MSFM) was introduced to improve its accuracy by solving the equation for a set of stencils and choosing the best solution at each considered node. The following work proposes a modified numerical scheme for MSFM to take into account the variation of the local cost, which has proven to be second order. The influence of the stencil set choice on the algorithm outcome with respect to stencil orthogonality and axis swapping is also explored, where stencils are taken from neighborhoods of varying radius. The experimental results show that the proposed schemes improve the accuracy of their original counterparts, and that the use of permutation-invariant stencil sets provides robustness against shifted vector coordinates in the stencil set.</p>
},
	keywords = {Approximation algorithms, Differential equations, Eikonal equation, Frequency modulation, MSFM, Mathematical model, Silicon, Three-dimensional displays, Unmanned aerial vehicles, Vectors, axis swapping, difference equations, fast marching methods, finite difference methods, finite differences, image processing, iterative methods, least squares approximations, multi-stencil schemes, multistencil version, nonconstant local cost model, permutation-invariant stencil sets, second order multistencil fast marching method, stencil orthogonality, stencil set},
	issn = {1057-7149},
	doi = {10.1109/TIP.2018.2880507},
	url = {https://ieeexplore.ieee.org/document/8531783/},
	author = {S. Merino-Caviedes and Lucilio Cordero-Grande and M. T. P{\'e}rez and Pablo Casaseca-de-la-Higuera and M. Mart{\'\i}n-Fern{\'a}ndez and R. Deriche and C. Alberola-L{\'o}pez}
}
