Overview of the HECKTOR challenge at MICCAI 2021: automatic head and neck tumor segmentation and outcome prediction in PET/CT images

V Andrearczyk, V Oreiller, S Boughdad… - 3D head and neck tumor …, 2021 - Springer
This paper presents an overview of the second edition of the HEad and neCK TumOR
(HECKTOR) challenge, organized as a satellite event of the 24th International Conference …

Semi-supervised 3D-InceptionNet for segmentation and survival prediction of head and neck primary cancers

A Qayyum, M Mazher, T Khan, I Razzak - Engineering Applications of …, 2023 - Elsevier
Cancers, known collectively as head and neck cancers, usually begin in the squamous cells
that line the head and neck's mucosal surfaces, forming a tumour mass. It usually develops …

[HTML][HTML] Automatic head and neck tumor segmentation and outcome prediction relying on FDG-PET/CT images: findings from the second edition of the HECKTOR …

V Andrearczyk, V Oreiller, S Boughdad… - Medical Image …, 2023 - Elsevier
By focusing on metabolic and morphological tissue properties respectively,
FluoroDeoxyGlucose (FDG)-Positron Emission Tomography (PET) and Computed …

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

L Rebaud, T Escobar, F Khalid, K Girum… - 3D Head and Neck Tumor …, 2022 - Springer
Automated lesion detection and segmentation might assist radiation therapy planning and
contribute to the identification of prognostic image-based biomarkers towards personalized …

[HTML][HTML] Deep learning-based outcome prediction using PET/CT and automatically predicted probability maps of primary tumor in patients with oropharyngeal cancer

A De Biase, B Ma, J Guo, LV van Dijk… - Computer Methods and …, 2024 - Elsevier
Abstract Background and Objective Recently, deep learning (DL) algorithms showed to be
promising in predicting outcomes such as distant metastasis-free survival (DMFS) and …

Radiomics-enhanced deep multi-task learning for outcome prediction in head and neck cancer

M Meng, L Bi, D Feng, J Kim - 3D Head and Neck Tumor Segmentation in …, 2022 - Springer
Outcome prediction is crucial for head and neck cancer patients as it can provide prognostic
information for early treatment planning. Radiomics methods have been widely used for …

Radiomics prognostic analysis of PET/CT images in a multicenter head and neck cancer cohort: Investigating ComBat strategies, sub-volume characterization, and …

H Xu, N Abdallah, JM Marion, P Chauvet… - European Journal of …, 2023 - Springer
Purpose This study aimed to investigate the impact of several ComBat harmonization
strategies, intra-tumoral sub-volume characterization, and automatic segmentations for …

Segmentation-free outcome prediction from head and neck cancer PET/CT images: Deep learning-based feature extraction from Multi-Angle Maximum Intensity …

A Toosi, I Shiri, H Zaidi, A Rahmim - Cancers, 2024 - pmc.ncbi.nlm.nih.gov
Simple Summary Head and neck cancer is a serious health concern that affects millions of
people across the globe. Predicting how patients will respond to therapy is critical for …

Longitudinal and multimodal radiomics models for head and neck cancer outcome prediction

S Starke, A Zwanenburg, K Leger, K Zöphel, J Kotzerke… - Cancers, 2023 - mdpi.com
Simple Summary Machine learning based radiomics models for prediction of loco-regional
recurrence today mostly rely on features extracted from pre-treatment imaging data. In this …

[HTML][HTML] Functional-structural sub-region graph convolutional network (FSGCN): application to the prognosis of head and neck cancer with PET/CT imaging

W Lv, Z Zhou, J Peng, L Peng, G Lin, H Wu… - Computer Methods and …, 2023 - Elsevier
Background and objective Accurate risk stratification is crucial for enabling personalized
treatment for head and neck cancer (HNC). Current PET/CT image-based prognostic …