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 …
(HECKTOR) challenge, organized as a satellite event of the 24th International Conference …
Fusion-based tensor radiomics using reproducible features: application to survival prediction in head and neck cancer
MR Salmanpour, M Hosseinzadeh, SM Rezaeijo… - Computer Methods and …, 2023 - Elsevier
Background Numerous features are commonly generated in radiomics applications as
applied to medical imaging, and identification of robust radiomics features (RFs) can be an …
applied to medical imaging, and identification of robust radiomics features (RFs) can be an …
Prediction of Cognitive decline in Parkinson's Disease using clinical and DAT SPECT Imaging features, and Hybrid Machine Learning systems
M Hosseinzadeh, A Gorji, A Fathi Jouzdani… - Diagnostics, 2023 - mdpi.com
Background: We aimed to predict Montreal Cognitive Assessment (MoCA) scores in
Parkinson's disease patients at year 4 using handcrafted radiomics (RF), deep (DF), and …
Parkinson's disease patients at year 4 using handcrafted radiomics (RF), deep (DF), and …
Deep versus handcrafted tensor radiomics features: prediction of survival in head and neck cancer using machine learning and fusion techniques
MR Salmanpour, SM Rezaeijo, M Hosseinzadeh… - Diagnostics, 2023 - mdpi.com
Background: Although handcrafted radiomics features (RF) are commonly extracted via
radiomics software, employing deep features (DF) extracted from deep learning (DL) …
radiomics software, employing deep features (DF) extracted from deep learning (DL) …
Semi-supervised 3D-InceptionNet for segmentation and survival prediction of head and neck primary cancers
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 …
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 …
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
Automated lesion detection and segmentation might assist radiation therapy planning and
contribute to the identification of prognostic image-based biomarkers towards personalized …
contribute to the identification of prognostic image-based biomarkers towards personalized …
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 …
strategies, intra-tumoral sub-volume characterization, and automatic segmentations for …
[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 …
treatment for head and neck cancer (HNC). Current PET/CT image-based prognostic …
Multi-Level fusion graph neural network: Application to PET and CT imaging for risk stratification of head and neck cancer
Background and objective Risk stratification of head and neck cancer (HNC) patients is
important to settle individualized treatment strategies. This study proposed a multi-level …
important to settle individualized treatment strategies. This study proposed a multi-level …