Daniel Di Giovanni

dblp:249/6966 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 2020
—ORCID · none

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

Artificial intelligence and machine learning · 2 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 2 · 1 first-authorGraphics, 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
Virtual and augmented reality · 60% Visualization and visual analytics · 20% Rendering · 20%
Human-computer interaction and pervasive computing
1 paper
Interaction techniques and input · 100%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Virtual and augmented reality
augmented reality
0.412020
Interaction Driven Enhancement of Depth Perception in Angiographic Volumes · IEEE Trans. Vis. Comput. Graph. 2020
Virtual and augmented reality
depth sensation enhancement
0.412020
Interaction Driven Enhancement of Depth Perception in Angiographic Volumes · IEEE Trans. Vis. Comput. Graph. 2020
Virtual and augmented reality › medical virtual reality
intraoperative visualization
0.412020
Interaction Driven Enhancement of Depth Perception in Angiographic Volumes · IEEE Trans. Vis. Comput. Graph. 2020
Visualization and visual analytics
medical visualization
0.412020
Interaction Driven Enhancement of Depth Perception in Angiographic Volumes · IEEE Trans. Vis. Comput. Graph. 2020
Rendering
volume rendering
0.412020
Interaction Driven Enhancement of Depth Perception in Angiographic Volumes · IEEE Trans. Vis. Comput. Graph. 2020

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

psychophysics experiment · 0.9dynamic depth cues · 0.9
YearPublicationVenuePosition
2020 Interaction Driven Enhancement of Depth Perception in Angiographic Volumes
abstract
User interaction has the potential to greatly facilitate the exploration and understanding of 3D medical images for diagnosis and treatment. However, in certain specialized environments such as in an operating room (OR), technical and physical constraints such as the need to enforce strict sterility rules, make interaction challenging. In this paper, we propose to facilitate the intraoperative exploration of angiographic volumes by leveraging the motion of a tracked surgical pointer, a tool that is already manipulated by the surgeon when using a navigation system in the OR. We designed and implemented three interactive rendering techniques based on this principle. The benefit of each of these techniques is compared to its non-interactive counterpart in a psychophysics experiment where 20 medical imaging experts were asked to perform a reaching/targeting task while visualizing a 3D volume of angiographic data. The study showed a significant improvement of the appreciation of local vascular structure when using dynamic techniques, while not having a negative impact on the appreciation of the global structure and only a marginal impact on the execution speed. A qualitative evaluation of the different techniques showed a preference for dynamic chroma-depth in accordance with the objective metrics but a discrepancy between objective and subjective measures for dynamic aerial perspective and shading.
Simon Drouin, Daniel Di Giovanni, Marta Kersten-Oertel, D. Louis Collins
IEEE Trans. Vis. Comput. Graph.2
2019 Assessment of Cognitive Load in the Context of Neurosurgery
Daniel Di Giovanni, Simon Drouin, Marta Kersten-Oertel, D. Louis Collins
CogSci1
2019 Detecting presupposition failure with EEG
Alice Xia, Roxana-Maria Barbu, Kathleen Van Benthem, Daniel Di Giovanni, Ida Toivonen, Raj Singh
CogSci4