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Hadi Fayad

dblp:14/7980 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2019
0000-0002-8780-230XORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Image and video processing · 100%
Artificial intelligence
1 paper
Segmentation and scene understanding · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video processing › image filtering › nonlinear diffusion
anisotropic diffusion
0.412019
Image Enhancement With PDEs and Nonconservative Advection Flow Fields · IEEE Trans. Image Process. 2019
Image and video processing
image enhancement
0.412019
Image Enhancement With PDEs and Nonconservative Advection Flow Fields · IEEE Trans. Image Process. 2019
Image and video processing
image restoration
0.412019
Image Enhancement With PDEs and Nonconservative Advection Flow Fields · IEEE Trans. Image Process. 2019
Image and video processing › image filtering
shock filter
0.412019
Image Enhancement With PDEs and Nonconservative Advection Flow Fields · IEEE Trans. Image Process. 2019
Computer vision › Segmentation and scene understanding
edge detection
0.112019
Image Enhancement With PDEs and Nonconservative Advection Flow Fields · IEEE Trans. Image Process. 2019

Methods — techniques the papers use, named apart from their topics

shock filtering · 0.8partial differential equations · 0.8nonconservative advection · 0.8
YearPublicationVenuePosition
2019 Image Enhancement With PDEs and Nonconservative Advection Flow Fields
abstract
We propose a new method for the progressive enhancement of images degraded by noise and blur using shock filters. The originality of our approach lies in the iterative exploitation of nonconservative edge-based force fields normally designed for segmentation to determine both locations and amplitudes of the sharpening action. The proposed nonconservative shock filter (NCSF) produces images with strong discontinuities that can be used as an additional pre-processing step to facilitate higher level tasks such as edge detection or segmentation. NCSF is especially useful when coupled with an anisotropic diffusion equation in noisy configurations. Using the proposed method, edges that are not well defined prior to filtering can be iteratively recovered. We show processing results on various types of images, focusing on medical transrectal ultrasound and brain PET imaging.
Vincent Jaouen, Julien Bert, Nicolas Boussion, Hadi Fayad, Mathieu Hatt, Dimitris Visvikis
IEEE Trans. Image Process.4
2018 The first MICCAI challenge on PET tumor segmentation
Mathieu Hatt, Baptiste Laurent, Anouar Ouahabi, Hadi Fayad, Tan Shan, Laquan Li, Wei Lu 0025, Vincent Jaouen, Clovis Tauber, Jakub Czakon, Filip Drapejkowski, Witold Dyrka, Sorina Camarasu-Pop, Frederic Cervenansky, Pascal Girard, Tristan Glatard, Michaël Kain, Christian Barillot, Assen Kirov, Dimitris Visvikis
Medical Image Anal.4
2017 MR-based respiratory and cardiac motion correction for PET imaging
Thomas Kustner, Martin Schwartz, Petros Martirosian, Sergios Gatidis, Ferdinand Seith, Christopher Gilliam, Thierry Blu, Hadi Fayad, Dimitris Visvikis, Fritz Schick, Bin Yang 0009, Nina F. Schwenzer
Medical Image Anal.8