Demo Data from SIGIR 2026 / reviewers in the wild / expert
Ângela Vilhena Dias
dblp:07/3367 · also Ángela Vilhena Dias
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2007
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Graphics, 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.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Medical and health informatics · 100% | |
| Computer graphics and multimedia
1 paper |
Image and video processing · 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
cardiac image analysis |
0.1 | 1 | 2007 | Interactive Left Ventricular Segmentation in Cardiac Images · ICCV 2007 |
Medical and health informatics › cardiac image analysis
left ventricle segmentation |
0.1 | 1 | 2007 | Interactive Left Ventricular Segmentation in Cardiac Images · ICCV 2007 |
Image and video processing
image segmentation |
0.1 | 1 | 2007 | Interactive Left Ventricular Segmentation in Cardiac Images · ICCV 2007 |
Image and video processing › image segmentation
interactive segmentation |
0.1 | 1 | 2007 | Interactive Left Ventricular Segmentation in Cardiac Images · ICCV 2007 |
Methods — techniques the papers use, named apart from their topics
region intensity feature · 0.1proximity feature · 0.1live-wire · 0.1edge-based segmentation · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2007 | Interactive Left Ventricular Segmentation in Cardiac ImagesabstractThis work presents a technique to perform segmentation of the left ventricle in images of the human myocardium. Segmentation is one of the first steps of the image analysis. Edge-based segmentation provides the detection of region boundaries, but the contours are only based on local computations, and is often sensitive to local variations in intensity, noise and physical artifacts. In interactive methods, problems like these fatigue the user and require many interventions at the contour delineation process. To reduce these problems, we propose the addition of two new features in the Live-Wire method: a region intensity and a proximity feature. Experimental results show that this alternative approach can achieve accurate edge localization and improved efficiency. Wendeson da Silva Oliveira, Ângela Vilhena Dias |
ICCV | 2 |