In recent years, groundbreaking foundation models such as GPT and SAM (Segment Anything Model, designed for visual tasks) have revolutionized the landscape of artificial intelligence (AI). However, it’s widely recognized in the field of medical image analysis that the remarkable capabilities of these general domain models often require adaptation for tasks involving medical imagery. To bridge this gap, techniques such as transfer learning are frequently employed to tailor these models to the specific requirements of medical imagery. This special session is dedicated to exploring effective strategies for integrating these expansive foundation models into the domain of medical image analysis. Specifically, it aims to uncover methods for medical AI researchers to leverage the extensive pre-trained knowledge of these models to enhance the effectiveness of medical image analysis.
We cordially invite submissions of papers that investigate the application of large foundation models (beyond just GPT or SAM) to the analysis of medical images, encompassing various modalities such as CT scans, X-rays, MRIs, PET scans, and ultrasounds. Submissions may address a range of tasks, including disease diagnosis (recognition and classification), quantification, and the detection or segmentation of lesions. We also encourage the exploration of recent medical foundation models such as MedSAM.
Organisers:
Dr Lin Yuanbo Wu (l.y.wu@swansea.ac.uk), Swansea University, UK.
Dr Bo Li (libo@nwpu.edu.cn), Northwestern Polytechnical University, China.
Dr Zhibin Liao (zhibin.liao@adelaide.edu.au), The University of Adelaide, Australia
Dr Sara Sharifzadeh (sara.sharifzadeh@swansea.ac.uk), Swansea University, UK
A/Prof. Benjamin Mora (b.mora@swansea.ac.uk), Swansea University, UK
Dr Yang Zhao (Y.Zhao2@latrobe.edu.au), La Trobe University, Australia
Prof. Zongyuan Ge (zongyuan.ge@monash.edu), Monash University, Australia
Submission format:
This special session welcomes both full length papers (12 pages plus up to 2 pages of references) and abstracts (up to 3 pages including references).
Deadline: All deadlines, including submission deadline and review timeline are the same as the main conference. Please follow this link to see all the Important Dates.
If you have any questions regarding this Special Session, please contact the organiser.