Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields

7 Oct 2016Patrick Ferdinand ChristMohamed Ezzeldin A. ElshaerFlorian EttlingerSunil TatavartyMarc BickelPatrick BilicMarkus RempflerMarco ArmbrusterFelix HofmannMelvin D'AnastasiWieland H. SommerSeyed-Ahmad AhmadiBjoern H. Menze

Automatic segmentation of the liver and its lesion 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 abdomen images using cascaded fully convolutional neural networks (CFCNs) and dense 3D conditional random fields (CRFs)... (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.