Head and Neck Tumor Segmentation and Outcome Prediction

Chapter 1 Overview of the HECKTOR Challenge at MICCAI 2022: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT

Chapter 2 Automated Head and Neck Tumor Segmentation from 3D PET/CT HECKTOR 2022 Challenge Report

Chapter 3 A Coarse-to-Fine Ensembling Framework for Head and Neck Tumor and Lymph Segmentation in CT and PET Images

Chapter 4 A General Web-Based Platform for Automatic Delineation of Head and Neck Gross Tumor Volumes in PET/CT Images

Chapter 5 Octree Boundary Transfiner: Efficient Transformers for Tumor Segmentation Refinement

Chapter 6 Head and Neck Primary Tumor and Lymph Node Auto-segmentation for PET/CT Scans

Chapter 7 Fusion-Based Automated Segmentation in Head and Neck Cancer via Advance Deep Learning Techniques

Chapter 8 Stacking Feature Maps of Multi-scaled Medical Images in U-Net for 3D Head and Neck Tumor Segmentation

Chapter 9 A Fine-Tuned 3D U-Net for Primary Tumor and Affected Lymph Nodes Segmentation in Fused Multimodal Images of Oropharyngeal Cancer

Chapter 10 A U-Net Convolutional Neural Network with Multiclass Dice Loss for Automated Segmentation of Tumors and Lymph Nodes from Head and Neck Cancer PET/CT Images

Chapter 12 Swin UNETR for Tumor and Lymph Node Segmentation Using 3D PET/CT Imaging: A Transfer Learning Approach

Chapter 13 Simplicity Is All You Need: Out-of-the-Box nnUNet Followed by Binary-Weighted Radiomic Model for Segmentation and Outcome Prediction in Head and Neck PET/CT

Chapter 14 Radiomics-Enhanced Deep Multi-task Learning for Outcome Prediction in Head and Neck Cancer

Chapter 15 Recurrence-Free Survival Prediction Under the Guidance of Automatic Gross Tumor Volume Segmentation for Head and Neck Cancers

Chapter 16 Joint nnU-Net and Radiomics Approaches for Segmentation and Prognosis of Head and Neck Cancers with PET/CT Images

Chapter 17 MLC at HECKTOR 2022: The Effect and Importance of Training Data When Analyzing Cases of Head and Neck Tumors Using Machine Learning

Chapter 18 Towards Tumour Graph Learning for Survival Prediction in Head & Neck Cancer Patients

Chapter 19 Combining nnUNet and AutoML for Automatic Head and Neck Tumor Segmentation and Recurrence-Free Survival Prediction in PET/CT Images

Chapter 20 Head and Neck Cancer Localization with Retina Unet for Automated Segmentation and Time-To-Event Prognosis from PET/CT Images

Chapter 21 HNT-AI: An Automatic Segmentation Framework for Head and Neck Primary Tumors and Lymph Nodes in FDG- PET/CT Images

Chapter 22 Head and Neck Tumor Segmentation with 3D UNet and Survival Prediction with Multiple Instance Neural Network

Chapter 23 Deep Learning and Machine Learning Techniques for Automated PET/CT Segmentation and Survival Prediction in Head and Neck Cancer

Chapter 24 Deep Learning and Radiomics Based PET/CT Image Feature Extraction from Auto Segmented Tumor Volumes for Recurrence-Free Survival Prediction in Oropharyngeal Cancer Patients