CVOct 6, 2023

Automated 3D Segmentation of Kidneys and Tumors in MICCAI KiTS 2023 Challenge

arXiv:2310.04110v134 citationsh-index: 46
Originality Synthesis-oriented
AI Analysis

This work addresses kidney and tumor segmentation for medical imaging researchers, but it is incremental as it applies an existing method to a new dataset.

The authors tackled the problem of automated 3D segmentation of kidneys and tumors in CT scans, achieving first place in the KiTS 2023 challenge with an average dice score of 0.835 and surface dice of 0.723.

Kidney and Kidney Tumor Segmentation Challenge (KiTS) 2023 offers a platform for researchers to compare their solutions to segmentation from 3D CT. In this work, we describe our submission to the challenge using automated segmentation of Auto3DSeg available in MONAI. Our solution achieves the average dice of 0.835 and surface dice of 0.723, which ranks first and wins the KiTS 2023 challenge.

Code Implementations1 repo
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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