AI-based detection, classification and prediction/prognosis in medical imaging: towards radiophenomics
The task of clinical interpretation of medical images starts with the scanning of the presented
image to detect the suspicious finding (“observation” in RadLex terminology (RID5) 1 which …
image to detect the suspicious finding (“observation” in RadLex terminology (RID5) 1 which …
Deep-learning 18F-FDG uptake classification enables total metabolic tumor volume estimation in diffuse large B-cell lymphoma
N Capobianco, M Meignan, AS Cottereau… - Journal of Nuclear …, 2021 - Soc Nuclear Med
Total metabolic tumor volume (TMTV), calculated from 18F-FDG PET/CT baseline studies, is
a prognostic factor in diffuse large B-cell lymphoma (DLBCL) whose measurement requires …
a prognostic factor in diffuse large B-cell lymphoma (DLBCL) whose measurement requires …
Detection and segmentation of lymphomas in 3D PET images via clustering with entropy-based optimization strategy
Purpose Lymphoma detection and segmentation from PET images are critical tasks for
cancer staging and treatment monitoring. However, it is still a challenge owing to the …
cancer staging and treatment monitoring. However, it is still a challenge owing to the …
Lymphoma segmentation in PET images based on multi-view and Conv3D fusion strategy
Due to the poor image information of lymphoma in PET images, it is still a challenge to
segment them correctly. In this work, a fusion strategy by 2D multi-view and 3D networks is …
segment them correctly. In this work, a fusion strategy by 2D multi-view and 3D networks is …
[HTML][HTML] Investigation of small lung lesion detection for lung cancer screening in low dose FDG PET imaging by deep neural networks
Purpose FDG PET imaging is often recommended for the diagnosis of pulmonary nodules
after indeterminate low dose CT lung cancer screening. Lowering FDG injecting is desirable …
after indeterminate low dose CT lung cancer screening. Lowering FDG injecting is desirable …
An automatic method to generate voxel-based absorbed doses from radioactivity distributions for nuclear medicine using generative adversarial networks: A feasibility …
H Lin, X Guo, J Jing, X Mao, Y Yang, M Hu - Physical and Engineering …, 2022 - Springer
An approach to autogenerate voxel-based absorbed dose for nuclear medicine is proposed
using generative adversarial networks. The method is based on image-to-image …
using generative adversarial networks. The method is based on image-to-image …
[HTML][HTML] Cancer imaging and image analysis methods in whole-body MRI and PET/MRI
T Sjöholm - 2023 - diva-portal.org
Cancer imaging and image analysis methods in whole-body MRI and PET/MRI diva-portal.org
Digitala Vetenskapliga Arkivet Planned maintenance A system upgrade is planned for 20/2-2024 …
Digitala Vetenskapliga Arkivet Planned maintenance A system upgrade is planned for 20/2-2024 …
Radiotracer uptake classification using deep learning for evaluation of image-derived cancer biomarkers in PET/CT
N Capobianco - 2022 - mediatum.ub.tum.de
Accurate assessment of disease spread is crucial in the care of cancer patients, and medical
imaging is frequently used as noninvasive diagnostic tool. This dissertation presents …
imaging is frequently used as noninvasive diagnostic tool. This dissertation presents …
[PDF][PDF] Haigen Hu, Pierre Decazes, Pierre Vera
H Li, S Ruan - researchgate.net
Purpose Lymphoma detection and segmentation from PET images are critical tasks for
cancer staging and treatment monitoring. However, it is still a challenge owing to the …
cancer staging and treatment monitoring. However, it is still a challenge owing to the …