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KiTS 2023 : The 2023 MICCAI Kidney Tumor Segmentation Challenge

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Link: https://kits-challenge.org/kits23/
 
When Oct 8, 2023 - Oct 12, 2023
Where Vancouver, Canada
Submission Deadline Jul 14, 2023
Notification Due Jul 28, 2023
Final Version Due Aug 11, 2023
Categories    machine learning   semantic segmentation   medical imaging   computer vision
 

Call For Papers

BACKGROUND

The 2023 Kidney and Kidney Tumor Segmentation challenge (abbreviated KiTS23) is a competition in which teams compete to develop the best system for automatic semantic segmentation of kidneys, renal tumors, and renal cysts. It is the third iteration of the KiTS challenge after having taken place in 2019 and 2021.

KiTS23 invites participants to develop a semantic segmentation model based on the training dataset that we have provided, and submit its test set predictions to us during the submission period. Crucially, KiTS23 also requires that participants submit a manuscript to describe their methodology. These manuscripts are very important in order to enable meta-analyses of which methods worked well and why.

These paper submissions will be presented at a satellite event of the 2023 International Conference on Medical Image Computing and Computer Assisted Interventions (MICCAI) taking place in Vancouver, Canada between October 8 and October 12, 2023. All submissions will undergo peer review to ensure that they describe the methods in adequate detail, and accepted papers will be published via Springer Nature as MICCAI satellite event proceedings.

The team with the top-performing segmentation model will be awarded $5,000 USD.


PROGRAM CHAIRS

- Nikolaos Papanikolopoulos, PhD, University of Minnesota
- Christopher Weight, MD, Cleveland Clinic


PROGRAM COMMITTEE

- Nicholas Heller, University of Minnesota
- Andrew Wood, MD, Cleveland Clinic
- Fabian Isensee, German Cancer Research Center
- Tim R├Ądsch, German Cancer Research Center
- Resha Tejpaul, University of Minnesota


CONTACT INFORMATION
If you have any questions, please contact Nicholas Heller at helle246@umn.edu

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