Automatic segmentation of liver tumors from multiphase contrast-enhanced CT images based on FCNs

[1]  Hayit Greenspan,et al.  Fully Convolutional Network for Liver Segmentation and Lesions Detection , 2016, LABELS/DLMIA@MICCAI.

[2]  Seyed-Ahmad Ahmadi,et al.  Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional Neural Networks and 3D Conditional Random Fields , 2016, MICCAI.

[3]  Jayaram K. Udupa,et al.  A general approach to liver lesion segmentation in CT images , 2016, SPIE Medical Imaging.

[4]  Said Ghnomiey.  Medical Image Segmentation Techniques: An Overview , 2016 .

[5]  Fucang Jia,et al.  Automatic Segmentation of Liver Tumor in CT Images with Deep Convolutional Neural Networks , 2015 .

[6]  L. Schwartz,et al.  Semiautomatic segmentation of liver metastases on volumetric CT images. , 2015, Medical physics.

[7]  E. Søfteland,et al.  Effect of the World Health Organization checklist on patient outcomes: a stepped wedge cluster randomized controlled trial. , 2015, Annals of surgery.

[8]  Hao Chen,et al.  Standard Plane Localization in Fetal Ultrasound via Domain Transferred Deep Neural Networks , 2015, IEEE Journal of Biomedical and Health Informatics.

[9]  Wei Zhao,et al.  Development of solid-state avalanche amorphous selenium for medical imaging. , 2015, Medical physics.

[10]  Trevor Darrell,et al.  Fully Convolutional Networks for Semantic Segmentation , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  H. Won,et al.  Automatic detection method of hepatocellular carcinomas using the non-rigid registration method of multi-phase liver CT images. , 2015, Journal of X-ray science and technology.

[12]  Simone Moreira de Macêdo,et al.  The role of renin-angiotensin system modulation on treatment and prevention of liver diseases , 2014, Peptides.

[13]  Bülent Yilmaz,et al.  Liver fibrosis staging using CT image texture analysis and soft computing , 2014, Appl. Soft Comput..

[14]  Xiaogang Wang,et al.  Fully Convolutional Neural Networks for Crowd Segmentation , 2014, ArXiv.

[15]  Zhiping Lin,et al.  Random feature subspace ensemble based Extreme Learning Machine for liver tumor detection and segmentation , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[16]  Bongyong Song,et al.  Development and operation of a prototype cone-beam computed tomography system for X-ray medical imaging , 2014 .

[17]  Jun Du,et al.  An Experimental Study on Speech Enhancement Based on Deep Neural Networks , 2014, IEEE Signal Processing Letters.

[18]  Xue-jia Hao,et al.  CT assessment of liver hemodynamics in patients with hepatocellular carcinoma after argon-helium cryoablation. , 2013, Hepatobiliary & pancreatic diseases international : HBPD INT.

[19]  E. Petre,et al.  Cholecystokinin-Assisted Hydrodissection of the Gallbladder Fossa during FDG PET/CT-guided Liver Ablation , 2013, CardioVascular and Interventional Radiology.

[20]  Yong Yin,et al.  A Likelihood and Local Constraint Level Set Model for Liver Tumor Segmentation from CT Volumes , 2013, IEEE Transactions on Biomedical Engineering.

[21]  Geoffrey E. Hinton,et al.  ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[22]  Ronald M. Summers,et al.  Liver and Tumor Segmentation and Analysis from CT of Diseased Patients via a Generic Affine Invariant Shape Parameterization and Graph Cuts , 2011, Abdominal Imaging.

[23]  Yoshua Bengio,et al.  Deep Sparse Rectifier Neural Networks , 2011, AISTATS.

[24]  Chunming Li,et al.  Distance Regularized Level Set Evolution and Its Application to Image Segmentation , 2010, IEEE Transactions on Image Processing.

[25]  László Ruskó,et al.  Automatic segmentation of the liver from multi- and single-phase contrast-enhanced CT images , 2009, Medical Image Anal..

[26]  Martin Styner,et al.  Comparison and Evaluation of Methods for Liver Segmentation From CT Datasets , 2009, IEEE Transactions on Medical Imaging.

[27]  S. Casciaro,et al.  A new fully automatic and robust algorithm for fast segmentation of liver tissue and tumors from CT scans , 2008, European Radiology.

[28]  Olga Veksler,et al.  Fast approximate energy minimization via graph cuts , 2001, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[29]  Jerry L. Prince,et al.  Snakes, shapes, and gradient vector flow , 1998, IEEE Trans. Image Process..

[30]  Yoshua Bengio,et al.  Gradient-based learning applied to document recognition , 1998, Proc. IEEE.