New Approach to Accelerated Image Annotation by Leveraging Virtual Reality and Cloud Computing

Corentin Guérinot (1, 2, 3) , Valentin Marcon (1) , Charlotte Godard (1, 4) , Thomas Blanc (3, 5) , Hippolyte Verdier (1) , Guillaume Planchon (1) , Francesca Raimondi (1, 6) , Nathalie Boddaert (6) , Mariana Alonso (2) , Kurt Sailor (2) , Pierre-Marie Lledo (2) , Bassam Hajj (5) , Mohamed El Beheiry (1) , Jean-Baptiste Masson (1)

1 Décision et processus Bayesiens - Decision and Bayesian Computation
2 Perception et Mémoire / Perception and Memory
3 Collège Doctoral
4 PSL - Université Paris Sciences et Lettres
5 PCC - Laboratoire Physico-Chimie Curie [Institut Curie]
6 Hôpital Necker - Enfants Malades [AP-HP]

Three-dimensional imaging is at the core of medical imaging and is becoming a standard in biological research. As a result, there is an increasing need to visualize, analyze and interact with data in a natural three-dimensional context. By combining stereoscopy and motion tracking, commercial virtual reality (VR) headsets provide a solution to this critical visualization challenge by allowing users to view volumetric image stacks in a highly intuitive fashion. While optimizing the visualization and interaction process in VR remains an active topic, one of the most pressing issue is how to utilize VR for annotation and analysis of data. Annotating data is often a required step for training machine learning algorithms. For example, enhancing the ability to annotate complex three-dimensional data in biological research as newly acquired data may come in limited quantities. Similarly, medical data annotation is often time-consuming and requires expert knowledge to identify structures of interest correctly. Moreover, simultaneous data analysis and visualization in VR is computationally demanding. Here, we introduce a new procedure to visualize, interact, annotate and analyze data by combining VR with cloud computing. VR is leveraged to provide natural interactions with volumetric representations of experimental imaging data. In parallel, cloud computing performs costly computations to accelerate the data annotation with minimal input required from the user. We demonstrate multiple proof-of-concept applications of our approach on volumetric fluorescent microscopy images of mouse neurons and tumor or organ annotations in medical images.

Mots clés: virtual reality; cloud computation; one-shot learning; inference; human-in-the-loop; MRI; CT-scan

Domaines: Informatique [cs]

Corentin Guérinot, Valentin Marcon, Charlotte Godard, Thomas Blanc, Hippolyte Verdier, et al.. New Approach to Accelerated Image Annotation by Leveraging Virtual Reality and Cloud Computing. Frontiers in Bioinformatics, 2022, 1, pp.777101. ⟨10.3389/fbinf.2021.777101⟩. ⟨hal-03795778⟩