Demo Data from EDBT 2026 / reviewers in the wild / expert
Naoyuki Shono
dblp:187/9616
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2018
0000-0002-4968-6168ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Graphics, computer vision, multimedia, augmented reality and games · 1Human-computer interaction and ubiquitous computing · 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.
| Human-computer interaction and pervasive computing
1 paper |
Interaction techniques and input · 100% | |
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visualization and visual analytics › volume visualization
medical volume visualization |
0.1 | 1 | 2016 | Interactive Volume Segmentation with Threshold Field Painting · UIST 2016 |
Methods — techniques the papers use, named apart from their topics
threshold field · 0.5flood fill · 0.5brush-based painting · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Real-time virtual brain aneurysm clipping surgeryabstractWe propose a fast, interactive real-time 3DCG deformable simulation prototype for preoperative virtual practice of brain aneurysm clipping surgery, controlled by Position Based Dynamics (PBD). Blood vessels are reconstructed from their central lines, connected to the brain by automatically generated thin threads "virtual trabeculae", and colored by automatically estimated their dominant region. Hirofumi Seo, Naoyuki Shono, Taichi Kin, Takeo Igarashi |
VRST | 2 |
| 2016 | Interactive Volume Segmentation with Threshold Field PaintingabstractAn interactive method for segmentation and isosurface extraction of medical volume data is proposed. In conventional methods, users decompose a volume into multiple regions iteratively, segment each region using a threshold, and then manually clean the segmentation result by removing clutter in each region. However, this is tedious and requires many mouse operations from different camera views. We propose an alternative approach whereby the user simply applies painting operations to the volume using tools commonly seen in painting systems, such as flood fill and brushes. This significantly reduces the number of mouse and camera control operations. Our technical contribution is in the introduction of the threshold field, which assigns spatially-varying threshold values to individual voxels. This generalizes discrete decomposition of a volume into regions and segmentation using a constant threshold in each region, thereby offering a much more flexible and efficient workflow. This paper describes the details of the user interaction and its implementation. Furthermore, the results of a user study are discussed. The results indicate that the proposed method can be a few times faster than a conventional method. Takeo Igarashi, Naoyuki Shono, Taichi Kin, Toki Saito |
UIST | 2 |