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Project ID: P202205230001
HECKTOR challenge- 2022 Task 2: The prediction of patient outcomes, namely Relapse-Free Survival (RFS) from the FDG-PET/CT images and available clinical data.
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Supervisor: Mohammadreza Salmanpour
Fund: Free
Status: on_going 4
Skills:

Deep Learning, Machine Learning, Image Processing

Requirements:

Machine Learning/ Deep learning (MATLAB\Python) Medical Image expert Radiomics Feature extraction


This project includes:
Advisors:
Mentors:
Members:

Description:

Following the success of the first two editions of the HECKTOR challenge in 2020 and 2021, this challenge will be presented at the 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2022. Two tasks are proposed this year (participants can choose to participate in either or both tasks): Task 1: The automatic segmentation of Head and Neck (H&N) primary tumors and lymph nodes (new!) in FDG-PET/CT images; Task 2: The prediction of patient outcomes, namely Relapse-Free Survival (RFS) from the FDG-PET/CT images and available clinical data.

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