1 code implementation • 2 Apr 2024 • Vinkle Srivastav, Keqi Chen, Nicolas Padoy
Unlike current state-of-the-art fully-supervised methods, our approach does not require any 2d or 3d ground-truth poses and uses only the multi-view input images from a calibrated camera setup and 2d pseudo poses generated from an off-the-shelf 2d human pose estimator.
no code implementations • 22 Feb 2024 • Jamshid Hassanpour, Vinkle Srivastav, Didier Mutter, Nicolas Padoy
In this work, we investigate the application of contrastive learning to the domain of medical image analysis.
no code implementations • 19 Dec 2023 • Idris Hamoud, Muhammad Abdullah Jamal, Vinkle Srivastav, Didier Mutter, Nicolas Padoy, Omid Mohareri
Surgical robotics holds much promise for improving patient safety and clinician experience in the Operating Room (OR).
2 code implementations • 15 Dec 2023 • Kun Yuan, Manasi Kattel, Joel L. Lavanchy, Nassir Navab, Vinkle Srivastav, Nicolas Padoy
We highlight that the primary limitation in the current surgical VQA systems is the lack of scene knowledge to answer complex queries.
no code implementations • 10 Dec 2023 • Deepak Alapatt, Aditya Murali, Vinkle Srivastav, Pietro Mascagni, AI4SafeChole Consortium, Nicolas Padoy
Methods: In this work, we employ self-supervised learning to flexibly leverage diverse surgical datasets, thereby learning taskagnostic representations that can be used for various surgical downstream tasks.
1 code implementation • 27 Jul 2023 • Kun Yuan, Vinkle Srivastav, Tong Yu, Joel L. Lavanchy, Pietro Mascagni, Nassir Navab, Nicolas Padoy
SurgVLP constructs a new contrastive learning objective to align video clip embeddings with the corresponding multiple text embeddings by bringing them together within a joint latent space.
1 code implementation • 1 Jul 2022 • Sanat Ramesh, Vinkle Srivastav, Deepak Alapatt, Tong Yu, Aditya Murali, Luca Sestini, Chinedu Innocent Nwoye, Idris Hamoud, Saurav Sharma, Antoine Fleurentin, Georgios Exarchakis, Alexandros Karargyris, Nicolas Padoy
Correct transfer of these methods to surgery, as described and conducted in this work, leads to substantial performance gains over generic uses of SSL - up to 7. 4% on phase recognition and 20% on tool presence detection - as well as state-of-the-art semi-supervised phase recognition approaches by up to 14%.
Ranked #1 on Semantic Segmentation on Endoscapes
1 code implementation • 26 Aug 2021 • Vinkle Srivastav, Afshin Gangi, Nicolas Padoy
Second, to address the domain shift and the lack of annotations, we propose a novel unsupervised domain adaptation method, called AdaptOR, to adapt a model from an in-the-wild labeled source domain to a statistically different unlabeled target domain.
1 code implementation • 28 Sep 2020 • Deepak Alapatt, Pietro Mascagni, Vinkle Srivastav, Nicolas Padoy
Deep neural networks power most recent successes of artificial intelligence, spanning from self-driving cars to computer aided diagnosis in radiology and pathology.
1 code implementation • 16 Jul 2020 • Vinkle Srivastav, Afshin Gangi, Nicolas Padoy
Human pose estimation (HPE) is a key building block for developing AI-based context-aware systems inside the operating room (OR).
1 code implementation • 16 Jul 2020 • Vinkle Srivastav, Afshin Gangi, Nicolas Padoy
2D/3D human pose estimation is needed to develop novel intelligent tools for the operating room that can analyze and support the clinical activities.
no code implementations • 16 Jul 2020 • Vinkle Srivastav, Britty Baby, Ramandeep Singh, Prem Kalra, Ashish Suri
The objective of the current study was to develop a modified version (Neuro-Endo-Trainer-Online Assessment System (NET-OAS)) by providing a stand-alone system with online evaluation and real-time feedback.
no code implementations • 29 Nov 2018 • Thibaut Issenhuth, Vinkle Srivastav, Afshin Gangi, Nicolas Padoy
Methods: We propose a comparison of 6 state-of-the-art face detectors on clinical data using Multi-View Operating Room Faces (MVOR-Faces), a dataset of operating room images capturing real surgical activities.
1 code implementation • 24 Aug 2018 • Vinkle Srivastav, Thibaut Issenhuth, Abdolrahim Kadkhodamohammadi, Michel de Mathelin, Afshin Gangi, Nicolas Padoy
In this paper, we present the dataset, its annotations, as well as baseline results from several recent person detection and 2D/3D pose estimation methods.