mlsanityData to 14 Oct 2026

Automated head and neck tumor segmentation from 3D PET/CT

arXiv 2209.10809 ↗First posted 22 Sep 2022eess.IV cs.CVcited by 9

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Abstract (arXiv)

Head and neck tumor segmentation challenge (HECKTOR) 2022 offers a platform for researchers to compare their solutions to segmentation of tumors and lymph nodes from 3D CT and PET images. In this work, we describe our solution to HECKTOR 2022 segmentation task. We re-sample all images to a common resolution, crop around head and neck region, and train SegResNet semantic segmentation network from MONAI. We use 5-fold cross validation to select best model checkpoints. The final submission is an ensemble of 15 models from 3 runs. Our solution (team name NVAUTO) achieves the 1st place on the HECKTOR22 challenge leaderboard with an aggregated dice score of 0.78802.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 3 of its 4 references that are in the map. First posted on arXiv 22 Sep 2022.

Builds on

3 of 4 references.

References · 3

  1. 2016Identity Mappings in Deep Residual Networkscited by 1,965
  2. 20183D MRI brain tumor segmentation using autoencoder regularizationcited by 328
  3. 2022Overview of the HECKTOR Challenge at MICCAI 2021: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT Imagescited by 30

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 5; 2025: 2; 2026: 1.

9 papers.

  1. 2024The 2024 Brain Tumor Segmentation (BraTS) Challenge: Glioma Segmentation on Post-treatment MRIcited by 69
  2. 2023Comprehensive framework for evaluation of deep neural networks in detection and quantification of lymphoma from PET/CT images: clinical insights, pitfalls, and observer agreement analysescited by 4
  3. 2024EDUE: Expert Disagreement-Guided One-Pass Uncertainty Estimation for Medical Image Segmentationcited by 2
  4. 2024AutoPET Challenge: Tumour Synthesis for Data Augmentationcited by 2
  5. 2025ENSAM: an efficient foundation model for interactive segmentation of 3D medical imagescited by 2
  6. 2024Interactive 3D Segmentation for Primary Gross Tumor Volume in Oropharyngeal Cancercited by 1
  7. 2024Comparative Analysis of nnUNet and MedNeXt for Head and Neck Tumor Segmentation in MRI-guided Radiotherapycited by 0
  8. 2025Comprehensive Evaluation of Quantitative Measurements from Automated Deep Segmentations of PSMA PET/CT Imagescited by 0
  9. 2026AMO-ENE: Attention-based Multi-Omics Fusion Model for Outcome Prediction in Extra Nodal Extension and HPV-associated Oropharyngeal Cancercited by 0