Deep learning models for automatic tumor segmentation and total tumor volume assessment in patients with colorectal liver metastases.
Nina J WesdorpJ Michiel ZeeuwSam C J PostmaJoran RoorJan Hein T M van WaesbergheJanneke E van den BerghIrene M NotaShira MoosRuby KemnaFijoy VadakkumpadanCourtney AmbrozicSusan van DierenMartinus J van AmerongenThiery ChapelleMarc R W EngelbrechtMichael F GerhardsDirk GrunhagenThomas M van GulikJohn J HermansKoert P de JongJoost M KlaaseMike S L LiemKrijn P van LiendenI Quintus MolenaarGijs A PatijnArjen M RijkenTheo M RuersCornelis VerhoefJohannes H W de WiltHenk A MarqueringJaap StokerRutger-Jan SwijnenburgCornelis J A PuntJoost HuiskensGeert KazemierPublished in: European radiology experimental (2023)
• Tumor response evaluation is time-consuming, manually performed, and ignores total tumor volume. • Automatic models can accurately segment tumors in patients with colorectal liver metastases. • Total tumor volume can be accurately calculated based on automatic segmentations.