Posts

Jonathan Shapey had the great honour to deliver the Hunterian Lecture at the Society of British Neurological Surgeons autumn congress (SBNS London 2023). Jonathan presented his work in developing a label-free real-time intraoperative hyperspectralimaging system for neurosurgery.

This video presents work lead by Martin Huber. Deep Homography Prediction for Endoscopic Camera Motion Imitation Learning investigates a fully self-supervised method for learning endoscopic camera motion from readily available datasets of laparoscopic interventions. The work addresses and tries to go beyond the common tool following assumption in endoscopic camera motion automation. This work will be presented at the 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023).

This video presents work lead by Mengjie Shi focusing on learning-based sound-speed correction for dual-modal photoacoustic/ultrasound imaging. This work will be presented at the 2023 IEEE International Ultrasonics Symposium (IUS).

You can read the preprint on arXiv: 2306.11034 and get the code from GitHub.

Recently, we organized a Public and Patient Involvement (PPI) group with Vestibular Schwannoma patients to understand their perspectives on an patient-centered automated report. Partnering with the British Acoustic Neuroma Association (BANA), we recruited participants by circulating a form within the BANA community through their social media platforms.

• Focus: Translational research on hyperspectral-based quantitative fluorescence imaging linked with a neurosurgery clinical study
• Line manager: Tom Vercauteren
• Clinical collaborator: King’s College Hospital
• Industry collaborator: Hypervision Surgical
• Salary: Grade 6, £41,386-£48,414 or Grade 7 £49,737-£55,306 per annum, including London Weighting Allowance

Job description

We are seeking an interventional image computing researcher to design and translate the next generation of AI-assisted hyperspectral imaging systems for surgical guidance using quantitative fluorescence. The postholder, based within the Department of Surgical & Interventional Engineering at King’s College London, will play a key role in NeuroPPEye a collaborative project with King’s College Hospital and work closely with the project’s industrial collaborator Hypervision Surgical, a King’s spin-out company. A clinical neurosurgery study underpins this collaboration. The successful candidate will work on the resulting neurosurgical data as well as controlled phantom data. They will also have the opportunity to provide insight on how to best acquire prospective data.

• Focus: Design principled approaches for trustworthy AI-enabled surgical assistance with a focus on real-time imaging data
• Line manager: Tom Vercauteren
• Salary: Grade 6 £41,386-£48,414 or Grade 7 £49,737-£55,306 per annum, including London Weighting Allowance

Job description

We are seeking a Post-doctoral Research Associate to develop novel trustworthy artificial intelligence (AI) algorithms able to extract actionable information from surgical imaging data.

This video presents work lead by Christopher E. Mower. OpTaS is an OPtimization-based TAsk Specification library for trajectory optimization and model predictive control. This work will be presented at the 2023 IEEE International Conference on Robotics and Automation (ICRA).

CAI4CAI members and alumni are leading the organization of the new edition of the cross-modality Domain Adaptation challenge (crossMoDA) for medical image segmentation Challenge, which will runs as an official challenge during the Medical Image Computing and Computer Assisted Interventions (MICCAI) 2023 conference.

The four co-founders of Hypervison Surgical, a King’s spin-out company, have been awarded the Cutlers’ Surgical Prize for outstanding work in the field of instrumentation, innovation and technical development.

The Cutlers’ Surgical Prize is one of the most prestigious annual prizes for original innovation in the design or application of surgical instruments, equipment or practice to improve the health and recovery of surgical patients.

This video presents work lead by Christopher E. Mower. OpTaS is an OPtimization-based TAsk Specification Python library for trajectory optimization and model predictive control. The code can be found at https://github.com/cmower/optas. This work will be presented at the 2023 IEEE International Conference on Robotics and Automation (ICRA).