Metabolic tumour volume in Hodgkin lymphoma—A comparison between manual and AI‐based analysis

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1. 1Automated quantification of reference levels in liver and mediastinal blood pool for the Deauville therapy response classification using <scp>FDG</scp>‐<scp>PET</scp>/<scp>CT</scp> in Hodgkin and non‐Hodgkin lymphomas2018 · 26 citations
2. 2Automated Segmentation of Baseline Metabolic Total Tumor Burden in Diffuse Large B-Cell Lymphoma: Which Method Is Most Successful? A Study on Behalf of the PETRA Consortium2020 · 110 citations
3. 3¹⁸F-FDG PET/CT Uptake Classification in Lymphoma and Lung Cancer by Using Deep Convolutional Neural Networks2019 · 217 citations
4. 4Convolutional Neural Networks for Automated PET/CT Detection of Diseased Lymph Node Burden in Patients with Lymphoma2020 · 71 citations
5. 5Artificial intelligence‐based detection of lymph node metastases by PET/CT predicts prostate cancer‐specific survival2020 · 31 citations