Demo Data from SIGIR 2026 / reviewers in the wild / expert
Winnok De Vos
dblp:169/0044 · also Winnok H. De Vos
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2018
0000-0003-0960-6781ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 2
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 · 50% Computational photography and imaging · 50% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Medical and health informatics · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Medical and health informatics › medical imaging
medical image analysis |
0.3 | 1 | 2018 | SliceMap: an algorithm for automated brain region annotation · Bioinform. 2018 |
Image and video processing
image registration |
0.2 | 1 | 2016 | BiDiFuse: a FIJI plugin for fusing bi-directionally recorded microscopic image volumes · Bioinform. 2016 |
Computational photography and imaging
microscopy imaging |
0.2 | 1 | 2016 | BiDiFuse: a FIJI plugin for fusing bi-directionally recorded microscopic image volumes · Bioinform. 2016 |
Medical and health informatics
neurodegenerative disease analysis |
0.1 | 1 | 2018 | SliceMap: an algorithm for automated brain region annotation · Bioinform. 2018 |
Methods — techniques the papers use, named apart from their topics
image registration · 0.3elastic registration · 0.3congealing · 0.3rigid transformation · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | SliceMap: an algorithm for automated brain region annotationabstractSummary: Many neurodegenerative disorders, such as Alzheimer's Disease, pertain to or spread from specific sites of the brain. Hence, accurate disease staging or therapy assessment in transgenic model mice demands automated analysis of selected brain regions. To address this need, we have developed an algorithm, termed SliceMap, that enables contextual quantification by mapping anatomical information onto microtome-cut brain slices. For every newly acquired high-resolution image of a brain slice, the algorithm performs a coarse congealing-based registration to a library of pre-annotated reference slices. A subset of optimally matching reference slices is then used for refined, elastic registration. Morphotextural metrics are used to measure registration performance and to automatically detect poorly cut slices. We have implemented our method as a plugin for FIJI image analysis freeware, and we have used it to regionally quantify tau pathology in brain slices from a tauopathy (P301S) mouse model. By enabling region-based quantification, our method contributes to a more accurate assessment of neurodegenerative disease development. Availability and implementation: The method is available as a plugin for FIJI from https://github.com/mbarbie1/SliceMap/, along with an example dataset and user instructions. Contact: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online. Michaël Barbier, Astrid Bottelbergs, Rony Nuydens, Andreas Ebneth, Winnok De Vos |
Bioinform. | 5 |
| 2016 | BiDiFuse: a FIJI plugin for fusing bi-directionally recorded microscopic image volumesabstractDeep tissue imaging is increasingly used for non-destructive interrogation of intact organs and small model organisms. An intuitive approach to increase the imaging depth by almost a factor of 2 is to record a sample from two sides and fuse both image stacks. However, imperfect three-dimensional alignment of both stacks presents a computational challenge. We have developed a FIJI plugin, called BiDiFuse, which merges bi-directionally recorded image stacks via 3D rigid transformations. The method is broadly applicable, considering it is compatible with all optical sectioning microscopes and it does not rely on fiducial markers for image registration. AVAILABILITY AND IMPLEMENTATION: The method is freely available as a plugin for FIJI from https://github.com/JanDetrez/BiDiFuse/ CONTACT: [email protected]. Jan R. Detrez, Jean-Marie Vanderwinden, Michaël Barbier, Marlies Verschuuren, Rony Nuydens, Xavier Langlois, Jean-Pierre Timmermans, Winnok De Vos |
Bioinform. | 8 |