Modified U-NET on CT images for automatic segmentation of liver and its tumor

Author:

Manjunath R.V.,Kwadiki Karibasappa

Publisher

Elsevier BV

Subject

General Medicine

Reference19 articles.

1. Fully automatic liver segmentation combining multi-dimensional graph cut with shape information in 3D CT images;Lu;Sci. Rep.,2018

2. H-DenseUNet: hybrid densely connected UNet for liver and tumor segmentation from CT volumes;Li;IEEE Trans. Med. Imag.,2018

3. ‘SegNet: a deep convolutional encoder-decoder architecture for robust semantic pixel-wise labelling;Badrinarayanan;Comput. Vis. Pattern Recognit.,2015

4. Accelerated liver tumor segmentation in four-phase computed tomography images;Chaieb;J. Real-Time Image Process.,2017

5. P. Luc, C. Couprie, S. Chintala, and J. Verbeek, ‘Semantic segmentation using adversarial networks,’’ 2016, arXiv:1611.08408. [Online]. Available: https://arxiv.org/abs/1611.08408.

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