Dataset Groups Activity Stream AutoPET 2022 challenge Tumor segmentation in PET-CT images is challenging due to the dual nature of the acquired information: low metabolic information in CT and low spatial resolution in PET. BibTex: @dataset{Simone_Bendazzoli_and_Mehdi_Astaraki_2024, abstract = {Tumor segmentation in PET-CT images is challenging due to the dual nature of the acquired information: low metabolic information in CT and low spatial resolution in PET.}, author = {Simone Bendazzoli and Mehdi Astaraki}, doi = {10.57702/2ko05ank}, institution = {No Organization}, keyword = {'Deep Learning', 'PET-CT', 'Tumor Segmentation'}, month = {dec}, publisher = {TIB}, title = {AutoPET 2022 challenge}, url = {https://service.tib.eu/ldmservice/dataset/autopet-2022-challenge}, year = {2024} }
