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CaPTion MICCAI2022 Workshop, 22nd September, 2022, Singapore

September 22

The Cancer Prevention Through early diagnosis (CaPTion) workshop invites researchers to submit their work in the field of medical imaging around the central theme of early cancer detection, and it strives to address the challenges that are required to be overcomed to translate computational methods to clinical practice through well designed, generalizable (robust), interpretable and clinically transferable methods. Most current methods are developed on retrospective data that do not guarantee good representation of daily clinical procedures (e.g. domain gap). Through this workshop, we aim to identify the new ecosystem that will enable comprehensive method validation and reliability of methods, setting up a new gold standard for sample size and elaborate evaluation strategies to identify failure modes of methods when applied to real-world clinical environments.

Workshop themes

  1. Early detection and diagnosis of cancer: learning algorithms for lesion detection in medical images, staging, risk assessment, prediction of cancer outcome (in terms of life expectancy, survivability, progression, treatment sensitivity)

  2. Image-guided therapy for cancer treatment: Image fusion, multi-modal registration, detection, segmentation, and tracking, computer-guided interventions, augmented reality for tumor delineation

  3. Real-world data exploration for cancer prediction: Big (imaging) data and analytics, active learning, semi and self-supervised learning, model-agnostic meta-learning, federated learning for (sparsely labeled) multi-center data.

  4. Cancer biomarkers: new predictive (visual) biomarker discovery in medical images, tumor data signatures, personalized cancer treatments, genomics and radiomics.

  5. Clinically accepted evaluation methods: Identifying new evaluation metrics or gold standards (e.g., compared to widely used Dice or IoU metrics), sample size standardization, best practices for validation, image simulation and synthesis techniques to train more robust deep learning models for cancer detection.

Important Dates
Paper submission begins: 2nd May 2022

Submission deadline: 25th June 2022

Paper decision notification: 16 July 2022

Camera ready submission: 30 July 2022

Workshop day: 22 September 2022

To find out more and to register click here.


September 22