- 2020
Mixed reality navigation system for ultrasound-guided percutaneous punctures: a pre-clinical evaluation
- Davrieux CF., Gimenez ME., Gonzalez CA., Ancel A., Guinin M., Fahrer B., Serra E., Kwak JM., Marescaux J., Hostettler A.
- 34
- 226-230
Surgical Data Science
Or scroll down for moreSurgical data science and team mission
Surgical Data Science (SDS) is about improving outcomes of surgery with AI-based software systems driven by clinical data. We aim to improve the training and capabilities of surgical teams with SDS, to reduce complications, make surgery easier and safer, and achieve better patient outcomes.
Disrumpere
Ultrasound (US) is a key technology to detect abdominal cancer early, and treat it with minimal intervention. The disrumpere project aims to combine low-cost ultrasound devices with innovative AI and robotics technologies, to make US easier, faster more widely used.
Laparoscopic surgical guidance systems with Augmented Reality
We research computer systems to improve laparoscopic surgery with Augmented Reality (AR) technologies. 3D medical image data such as CT or MR is automatically combined with the laparoscopic video, to show hidden critical structures such as tumours and major vessels.
Percutaneous surgical guidance systems
We research computer systems to improve percutaneous surgery with Virtual Reality (VR) and 3D tracking technologies.
Ultrasound and flexible endoscopy educational systems
Objective skill assessment is becoming an increasingly important component of surgery education and high-stakes skill assessment for accreditation. Our goal is to combine low-cost mechanical simulators with AI to make these tools broadly accessible.
Software
Sight
Sight, the Surgical Image Guidance and Healthcare Toolkit facilitates the creation of software based on medical imaging.
It includes various features such as 2D and 3D medical image processing (CT/MRI/US), video processing, visualization, augmented reality, and connectivity with tracking systems. It can be used to write navigation systems, simulators, planning software, or even simple video filtering applications.
Sight is written in C++ and built on top of the best open-source libraries in the field such as OpenCV, ITK, VTK, PCL, and Qt and makes their usage easier by providing data common formats and wrappers. It is based on a modular object/service architecture, making building software application as simple as connecting together data, algorithms and user interface. It runs on Windows and Linux and is freely available under the LGPL.
Visualisation
- Multi-Planar Reconstruction
- Direct volume rendering
- Mixed Rendering (Volume + Surfaces)
- OpenGL 4.x programmable pipeline
- Fast rendering pipeline
Formats and protocols
- DICOM CT/MRI images
- SCP/SCU
- OpenIGTLink
- Video files: MP4/AVI/MKV/…
- Cameras: Intel Realsense, most USB webcams.
- RTP/RTSP streaming
Fast prototyping
- Interface and application design with XML or QML files
- Reusable algorithms and widgets as services
- Modular code, dynamic library loading
- Easy application packaging
- Prebuilt binaries for 3rd part libraries
Augmented reality
- Camera calibration
- Lens distortion and undistortion compensation
- Virtual 2D/3D scene superimposition onto video
- Precise synchronisation of the video and the virtual layer
- Optical tracking with Aruco tags
Software applications
SightViewer
Medical image and segmentation viewer. It supports many popular formats including DICOM and VTK.
SightCalibrator
User-friendly application to calibrate mono and stereo cameras. Very handy since camera calibration is a prerequisite in any AR application.
Clinical and technical publications
- 2020
Artificial intelligence and surgery: Recent progress and future perspectives
- Collins T., Hostettler A., Marescaux J
- 19
- 118-127
- 2020
Automatic task recognition in a flexible endoscopy benchtop trainer with semi-supervised learning
- Bencteux V., Saibro G., Shlomovitz E., Mascagni P., Perretta S., Hostettler A., Marescaux J., Collins T.
- 2019
Light modelling and calibration in laparoscopy
- Modrzejewski R. Collins T., Hostettler A., Marescaux J., Bartoli A.
Datasets
Liver segmentation
3D-IRCADb-01
This dataset is composed of the CT-scans of 10 women and 10 men with hepatic tumors in 75% of cases.
Where appropriate, the Couinaud segment number corresponding to the location of tumors is also provided.
Respiratory cycle
3D-IRCADb-02
This dataset is composed of 2 anonymized CT-scans.
The first one has been realized during the arterial phase in inhaled position, whereas the second one has been realized during the portal phase in exhaled position.
The patient has a hepatic focal nodular hyperplasia in segment VII according to Couinaud’s description.
The DEPOLL dataset for evaluating registration accuracy in AR-guided liver surgery
DePoLL (the Deformable Porcine Laparoscopic Liver) dataset was created to quantitatively evaluate registration accuracy for AR-guided liver surgery using a pre-operative CT model.
Crew
Josiane Uwineza
Research engineer
Python, Data science, Machine learning, Deep learning, Computer vision, prayer
Didier WECKMANN
Senior software developer
C++, Python, Javascript, Software architecture, Continuous integration, science fanboy
Dr. Patrick Niyishaka
Research engineer
Python, data science, machine learning deep learning, computer vision, digital image processing, basketball and travel lover
Richard Nkusi
Research engineer
Data science, Machine learning, Deep learning, Computer vision, Believer
Yvonne Keeza
Medical Imaging Annotator
Medical image data analysis, radiology, ultrasound, project management, image protocol and annotations, medical technology enthusiast, salsa dancer
Grace Ufitinema
Medical Imaging Annotator
Medical image analysis, radiography, ultrasound, annotation, basketball-lover
Florien Ujemurwego
Medical Imaging Annotator
Medical image analysis, radiography, ultrasound,
annotation, medical image management, swimming-lover
Bereket Frezgiy
Research engineer
Machine learning, computer vision, Medical image analysis, deep learning and Research communication, cycling race world tours
Güinther Saibro
Phd. Student
Python, Deep learning, Statistics, Medical image analysis, Ultrasound, Cycling
William Ndzimbong
Phd. Student
Python, Matlab, deep learning, computer vision, numerical optimization, new culture hunter
Dr. Michael KUGLER
Research engineer
Mechanics, C++, Numerical optimization, Software engineering, Research communication
Careers
IRCAD Africa
C++ developer
- Develop new surgical navigation systems integrating our latest advances in AI.
- Develop new features and provide support on our open-source toolkit Sight.
Partners
