Efficient two-step liver and tumour segmentation on abdominal CT via deep learning and a conditional random field

Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data

John Lafferty, Andrew McCallum, Fernando C. N. Pereira · Scholarly Commons (University of Pennsylvania) · 2001 · 13K citations · Full text

Computing, Computer Science, Computational Linguistics +12

H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation From CT Volumes

Xiaomeng Li, Hao Chen, Xiaojuan Qi et al. · IEEE Transactions on Medical Imaging · 2018 · 2.5K citations

Computing, Oncology, Radiology +17

FractalNet: Ultra-Deep Neural Networks without Residuals

Gustav Larsson, Michael Maire, Gregory Shakhnarovich · arXiv (Cornell University) · 2016 · 622 citations · Full text

Computing, Computer Science, Artificial Intelligence +12

RA-UNet: A Hybrid Deep Attention-Aware Network to Extract Liver and Tumor in CT Scans

Qiangguo Jin, Zhaopeng Meng, Changming Sun et al. · Frontiers in Bioengineering and Biotechnology · 2020 · 460 citations · Full text

Computing, Biomedical Engineering, Radiology +17

A Novel Deep-Learning Model for Automatic Detection and Classification of Breast Cancer Using the Transfer-Learning Technique

Abeer Saber, Mohamed Sakr, Osama M. Abo-Seida et al. · IEEE Access · 2021 · 406 citations · Full text

Computing, Computer Science, Radiology +17