210 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Centre National de la Recherche ScientifiqueFR17 papers
- Université de StrasbourgFR17 papers
- Institut de Chirurgie Guidée par l'ImageFR12 papers
- Laboratoire des Sciences de l'Ingénieur, de l'Informatique et de l'ImagerieFR7 papers
- InsermFR6 papers
- Institut de Recherche contre les Cancers de l’Appareil DigestifFR6 papers
- Institut de Recherche Mathématique AvancéeFR3 papers
- Cornell UniversityUS2 papers
- Hôpital Civil, StrasbourgFR2 papers
- Université de Technologie de TroyesFR2 papers
- University of EdinburghGB2 papers
- Aarhus University HospitalDK1 paper
22 papers
KMT2B-related disorders: expansion of the phenotypic spectrum and long-term efficacy of deep brain stimulation
L Cif, D Demailly, JP Lin +112
Heterozygous mutations in KMT2B are associated with an early-onset, progressive, and often complex dystonia (DYT28). Key characteristics of typical disease include focal motor feat…
UltraSam: A Foundation Model for Ultrasound using Large Open-Access Segmentation Datasets
Adrien Meyer, Aditya Murali, Farahdiba Zarin +2
Purpose: Automated ultrasound image analysis is challenging due to anatomical complexity and limited annotated data. To tackle this, we take a data-centric approach, assembling the…
Detection Transformer for Teeth Detection, Segmentation, and Numbering in Oral Rare Diseases: Focus on Data Augmentation and Inpainting Techniques
Hocine Kadi, Théo Sourget, Marzena Kawczynski +3
In this work, we focused on deep learning image processing in the context of oral rare diseases, which pose challenges due to limited data availability. A crucial step involves tee…
Ultrasonic elastography for the prevention of breast implant rupture: Detection of an increase with stiffness over implantation time
Laetitia Ruffenach, Dimitri Heintz, Claire Villette +5
Breast implants are widely used after breast cancer resection and must be changed regularly to avoid a rupture. To date, there are no quantitative criteria to help this decision. T…
Blockchain as an IoT intermediary
M. Sipek, M. Zagar, B. Mihaljevic
Blockchain technology provides a private, secure, transparent decentralized exchange of data. Also, blockchain is not limited to a particular area, but it has a wide range of appli…
Rendezvous: Attention Mechanisms for the Recognition of Surgical Action Triplets in Endoscopic Videos
Chinedu Innocent Nwoye, Tong Yu, Cristians Gonzalez +5
Out of all existing frameworks for surgical workflow analysis in endoscopic videos, action triplet recognition stands out as the only one aiming to provide truly fine-grained and c…
Exploring convolutional neural networks with transfer learning for diagnosing Lyme disease from skin lesion images
Sk Imran Hossain, Jocelyn de Goër de Herve, Md Shahriar Hassan +16
Lyme disease which is one of the most common infectious vector-borne diseases manifests itself in most cases with erythema migrans (EM) skin lesions. Recent studies show that convo…
Investigation of PVC plastisol tissue-mimicking phantoms for MR-and ultrasound-elastography
Simon Chatelin, Elodie Breton, Ajeethan Arulrajah +4
Objective: Realistic tissue-mimicking phantoms are essential for the development, the investigation and the calibration of medical imaging techniques and protocols. Because it requ…
Self-supervision on Unlabelled OR Data for Multi-person 2D/3D Human Pose Estimation
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. The lack of annotated data and…
Human Pose Estimation on Privacy-Preserving Low-Resolution Depth Images
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). The 24/7 use of images coming from cameras mounted…
The reliability of a deep learning model in clinical out-of-distribution MRI data: a multicohort study
Gustav Mårtensson, Daniel Ferreira, Tobias Granberg +22
Deep learning (DL) methods have in recent years yielded impressive results in medical imaging, with the potential to function as clinical aid to radiologists. However, DL models in…
Face Detection in the Operating Room: Comparison of State-of-the-art Methods and a Self-supervised Approach
Thibaut Issenhuth, Vinkle Srivastav, Afshin Gangi +1
Purpose: Face detection is a needed component for the automatic analysis and assistance of human activities during surgical procedures. Efficient face detection algorithms can inde…
Weakly Supervised Convolutional LSTM Approach for Tool Tracking in Laparoscopic Videos
Chinedu Innocent Nwoye, Didier Mutter, Jacques Marescaux +1
Purpose: Real-time surgical tool tracking is a core component of the future intelligent operating room (OR), because it is highly instrumental to analyze and understand the surgica…
Future-State Predicting LSTM for Early Surgery Type Recognition
Siddharth Kannan, Gaurav Yengera, Didier Mutter +2
This work presents a novel approach for the early recognition of the type of a laparoscopic surgery from its video. Early recognition algorithms can be beneficial to the developmen…
Determining the Number of Components in PLS Regression on Incomplete Data
Titin Agustin Nengsih, Frédéric Bertrand, Myriam Maumy-Bertrand +1
Partial least squares regression---or PLS---is a multivariate method in which models are estimated using either the SIMPLS or NIPALS algorithm. PLS regression has been extensively…
selectBoost: a general algorithm to enhance the performance of variable selection methods in correlated datasets
Ismaïl Aouadi, Nicolas Jung, Raphael Carapito +4
Motivation: With the growth of big data, variable selection has become one of the major challenges in statistics. Although many methods have been proposed in the literature their p…
Weakly-Supervised Learning for Tool Localization in Laparoscopic Videos
Armine Vardazaryan, Didier Mutter, Jacques Marescaux +1
Surgical tool localization is an essential task for the automatic analysis of endoscopic videos. In the literature, existing methods for tool localization, tracking and segmentatio…
RSDNet: Learning to Predict Remaining Surgery Duration from Laparoscopic Videos Without Manual Annotations
Andru Putra Twinanda, Gaurav Yengera, Didier Mutter +2
Accurate surgery duration estimation is necessary for optimal OR planning, which plays an important role in patient comfort and safety as well as resource optimization. It is, howe…
The Detailed Science Case for the Maunakea Spectroscopic Explorer: the Composition and Dynamics of the Faint Universe
Alan McConnachie, Carine Babusiaux, Michael Balogh +173
MSE is an 11.25m aperture observatory with a 1.5 square degree field of view that will be fully dedicated to multi-object spectroscopy. More than 3200 fibres will feed spectrograph…
Articulated Clinician Detection Using 3D Pictorial Structures on RGB-D Data
Abdolrahim Kadkhodamohammadi, Afshin Gangi, Michel de Mathelin +1
Reliable human pose estimation (HPE) is essential to many clinical applications, such as surgical workflow analysis, radiation safety monitoring and human-robot cooperation. Propos…
EndoNet: A Deep Architecture for Recognition Tasks on Laparoscopic Videos
Andru P. Twinanda, Sherif Shehata, Didier Mutter +3
Surgical workflow recognition has numerous potential medical applications, such as the automatic indexing of surgical video databases and the optimization of real-time operating ro…
AcSel: selecting variables with accuracy in correlated datasets
Jung Nicolas, Frédéric Bertrand, Myriam Maumy-Bertrand
With the emergence of high-throughput technologies, it is possible to measure large amounts of data relatively at low cost. Such situations arise in many fields from sciences to hu…