Artificial intelligence and robot-assisted automation technologies are rapidly transforming the landscape of various domains including healthcare. Despite the increasing awareness of applying such latest technologies in surgery and minimally invasive procedures, the examples of domain-specific successful stories in healthcare still lag behind compared with other general fields such as autonomous driving. Building on the successful MICCAI 2025 edition, COLAS 2026 continues the series with a clearer focus on collaborative intelligence and autonomy in image-guided surgery, and aims to provide a forum within the MICCAI community to explore and discuss this emerging topic. The workshop will include classic CAI topics such as image-guided interventions, virtual/augmented reality, surgical planning, surgical workflow analysis, pre-/intraoperative image registration, surgical scene understanding, etc. In addition, we can also consider covering emerging topics at the intersection of machine learning and robotics for their application in surgery, such as surgical embodied intelligence, human-robot collaborative control in medical robotics, AI-assisted autonomy in image-guided surgery, etc. Open questions such as the role of intelligent surgical assistants in next-generation operating rooms, and the ethical implications of autonomous surgical systems will also be actively discussed. Besides, a dedicated Dataset Spotlight segment on important surgical datasets that are work-in-progress or have been created or substantially extended in the past year will be introduced. This workshop will bring together researchers, surgeons, and industry leaders to discuss the latest innovations and applications of the new technologies in enhancing surgical precision, skill learning, decision-making, and patient outcomes for surgery.

Call for Papers

Through this MICCAI Workshop on "COLlaborative Intelligence and Autonomy in Image-guided Surgery", we aim to bring together researchers, surgeons, and industry leaders to discuss the latest innovations and their practical applications in surgery. COLAS 2026 will continue this discussion while placing additional emphasis on collaborative intelligence, autonomy, and dataset-centric community building. 

Submission Categories

Category 1: Full Research Papers (for Publication and Presentation)

We invite full research papers presenting novel research, methodologies, or significant findings relevant to the COLAS workshop themes. This category welcomes: 

• Original, unpublished research.

• MICCAI (or other similiar venues) rejected papers that authors wish submit after addressing reviewers' minor feedback. 

Accepted papers will be published in the official MICCAI workshop proceedings as a Lecture Notes in Computer Science (LNCS) on Springer Nature and presented at the workshop.

Submission format: 8 pages + 2 pages reference in Springer LNCS format (following MICCAI2026 official Manuscript Preparation Guidelines).

Category 2: Extended Abstracts (for Presentation only)

We welcome extended abstracts reporting ongoing work, preliminary results, or valuable insights, whether these are technical studies, challenge reports, dataset descriptions, or novel ideas. This category is suitable for:

• Work-in-progress.

• Current challenges and dataset papers intended for discussion.

• Short summary of recently published papers (in other relevant venues such as medical robotics) that are interested to the community for sharing and discussion.

Accepted abstracts will be presented at the workshop but will not be included in the published proceedings. We look forward to welcoming more participants for idea sharing and discussion of future perspectives.

Submission format: 4 pages + 2 pages reference (Springer LNCS format).

Submission Guidelines

• Papers must be submitted in PDF format using the MICCAI 2026 LaTeX or MS Word template.

• Submissions are handled through the OpenReivew platform: [Submit]

• Papers must be anonymized for double-blind peer review

• Each submission will be evaluated by expert reviewers

• Authors must declare any conflicts of interest during submission