Automatic Liver and Tumor Segmentation of CT and MRI Volumes using Cascaded Fully Convolutional Neural Networks

20 Feb 2017Patrick Ferdinand ChristFlorian EttlingerFelix GrünMohamed Ezzeldin A. ElshaeraJana LipkovaSebastian SchlechtFreba AhmaddySunil TatavartyMarc BickelPatrick BilicMarkus RempflerFelix HofmannMelvin D AnastasiSeyed-Ahmad AhmadiGeorgios KaissisJulian HolchWieland SommerRickmer BrarenVolker HeinemannBjoern Menze

Automatic segmentation of the liver and hepatic lesions is an important step towards deriving quantitative biomarkers for accurate clinical diagnosis and computer-aided decision support systems. This paper presents a method to automatically segment liver and lesions in CT and MRI abdomen images using cascaded fully convolutional neural networks (CFCNs) enabling the segmentation of a large-scale medical trial or quantitative image analysis... (read more)

PDF Abstract

Evaluation Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.