Repeatability of two semi-automatic artificial intelligence approaches for tumor segmentation in PET

Positron emission tomography (PET) is routinely used for cancer staging and treatment follow-up. Metabolic active tumor volume (MATV) as well as total MATV (TMATV-including primary tumor, lymph nodes and metastasis) and/or total lesion glycolysis derived from PET images have been identified as prognostic factor or for the evaluation of treatment efficacy in cancer patients. To this end, a segmentation approach with high precision and repeatability is important. However, the implementation of a repeatable and accurate segmentation algorithm remains an ongoing challenge.

Publication year:2021

Keywords:Convolutional neural network, Repeatability, Textural segmentation, Tumor segmentation PET

BOF-keylabel:yes

IOF-keylabel:yes

BOF-publication weight:1

Authors:International

Authors from:Higher Education, Hospital

Accessibility:Open