Preparing medical imaging data for machine learning
Artificial intelligence (AI) continues to garner substantial interest in medical imaging. The
potential applications are vast and include the entirety of the medical imaging life cycle from …
potential applications are vast and include the entirety of the medical imaging life cycle from …
Machine and deep learning methods for radiomics
Radiomics is an emerging area in quantitative image analysis that aims to relate large‐scale
extracted imaging information to clinical and biological endpoints. The development of …
extracted imaging information to clinical and biological endpoints. The development of …
[HTML][HTML] Head and neck tumor segmentation in PET/CT: the HECKTOR challenge
V Oreiller, V Andrearczyk, M Jreige, S Boughdad… - Medical image …, 2022 - Elsevier
This paper relates the post-analysis of the first edition of the HEad and neCK TumOR
(HECKTOR) challenge. This challenge was held as a satellite event of the 23rd International …
(HECKTOR) challenge. This challenge was held as a satellite event of the 23rd International …
A whole-body fdg-pet/ct dataset with manually annotated tumor lesions
We describe a publicly available dataset of annotated Positron Emission Tomography/
Computed Tomography (PET/CT) studies. 1014 whole body Fluorodeoxyglucose (FDG) …
Computed Tomography (PET/CT) studies. 1014 whole body Fluorodeoxyglucose (FDG) …
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 …
[HTML][HTML] The applications of radiomics in precision diagnosis and treatment of oncology: opportunities and challenges
Medical imaging can assess the tumor and its environment in their entirety, which makes it
suitable for monitoring the temporal and spatial characteristics of the tumor. Progress in …
suitable for monitoring the temporal and spatial characteristics of the tumor. Progress in …
A radiomics approach to assess tumour-infiltrating CD8 cells and response to anti-PD-1 or anti-PD-L1 immunotherapy: an imaging biomarker, retrospective …
Background Because responses of patients with cancer to immunotherapy can vary in
success, innovative predictors of response to treatment are urgently needed to improve …
success, innovative predictors of response to treatment are urgently needed to improve …
AnatomyNet: deep learning for fast and fully automated whole‐volume segmentation of head and neck anatomy
Purpose Radiation therapy (RT) is a common treatment option for head and neck (HaN)
cancer. An important step involved in RT planning is the delineation of organs‐at‐risks …
cancer. An important step involved in RT planning is the delineation of organs‐at‐risks …
Radiomics in nuclear medicine: robustness, reproducibility, standardization, and how to avoid data analysis traps and replication crisis
A Zwanenburg - European journal of nuclear medicine and molecular …, 2019 - Springer
Radiomics in nuclear medicine is rapidly expanding. Reproducibility of radiomics studies in
multicentre settings is an important criterion for clinical translation. We therefore performed a …
multicentre settings is an important criterion for clinical translation. We therefore performed a …
[HTML][HTML] Vulnerabilities of radiomic signature development: the need for safeguards
Purpose Refinement of radiomic results and methodologies is required to ensure
progression of the field. In this work, we establish a set of safeguards designed to improve …
progression of the field. In this work, we establish a set of safeguards designed to improve …