![JPM | Free Full-Text | Multi-Resolution Image Segmentation Based on a Cascaded U-ADenseNet for the Liver and Tumors JPM | Free Full-Text | Multi-Resolution Image Segmentation Based on a Cascaded U-ADenseNet for the Liver and Tumors](https://www.mdpi.com/jpm/jpm-11-01044/article_deploy/html/images/jpm-11-01044-g008-550.jpg)
JPM | Free Full-Text | Multi-Resolution Image Segmentation Based on a Cascaded U-ADenseNet for the Liver and Tumors
![Deep learning and level set approach for liver and tumor segmentation from CT scans - Alirr - 2020 - Journal of Applied Clinical Medical Physics - Wiley Online Library Deep learning and level set approach for liver and tumor segmentation from CT scans - Alirr - 2020 - Journal of Applied Clinical Medical Physics - Wiley Online Library](https://aapm.onlinelibrary.wiley.com/cms/asset/f0106165-44dd-4aae-b617-550564e7474b/acm213003-fig-0001-m.jpg)
Deep learning and level set approach for liver and tumor segmentation from CT scans - Alirr - 2020 - Journal of Applied Clinical Medical Physics - Wiley Online Library
![The scans in Liver Tumor Segmentation Challenge (LiTS) 2017 dataset and... | Download Scientific Diagram The scans in Liver Tumor Segmentation Challenge (LiTS) 2017 dataset and... | Download Scientific Diagram](https://www.researchgate.net/publication/341806059/figure/fig2/AS:897787147333632@1591060544131/The-scans-in-Liver-Tumor-Segmentation-Challenge-LiTS-2017-dataset-and-3D-Image.png)
The scans in Liver Tumor Segmentation Challenge (LiTS) 2017 dataset and... | Download Scientific Diagram
Clinical application of mask region-based convolutional neural network for the automatic detection and segmentation of abnormal liver density based on hepatocellular carcinoma computed tomography datasets | PLOS ONE
![A study of generalization and compatibility performance of 3D U-Net segmentation on multiple heterogeneous liver CT datasets | BMC Medical Imaging | Full Text A study of generalization and compatibility performance of 3D U-Net segmentation on multiple heterogeneous liver CT datasets | BMC Medical Imaging | Full Text](https://media.springernature.com/lw685/springer-static/image/art%3A10.1186%2Fs12880-021-00708-y/MediaObjects/12880_2021_708_Fig4_HTML.png)
A study of generalization and compatibility performance of 3D U-Net segmentation on multiple heterogeneous liver CT datasets | BMC Medical Imaging | Full Text
![Segmentation automatique des métastases hépatiques en imagerie TEP/TDM basée sur l'apprentissage profond dans le cadre du cancer du sein métastatique Segmentation automatique des métastases hépatiques en imagerie TEP/TDM basée sur l'apprentissage profond dans le cadre du cancer du sein métastatique](https://blog.keosys.com/hubfs/0001-min1.jpg)
Segmentation automatique des métastases hépatiques en imagerie TEP/TDM basée sur l'apprentissage profond dans le cadre du cancer du sein métastatique
![Deep Learning for Automated Segmentation of Liver Lesions at CT in Patients with Colorectal Cancer Liver Metastases | Radiology: Artificial Intelligence Deep Learning for Automated Segmentation of Liver Lesions at CT in Patients with Colorectal Cancer Liver Metastases | Radiology: Artificial Intelligence](https://pubs.rsna.org/cms/10.1148/ryai.2019180014/asset/images/medium/ryai.2019180014.fig1.gif)
Deep Learning for Automated Segmentation of Liver Lesions at CT in Patients with Colorectal Cancer Liver Metastases | Radiology: Artificial Intelligence
![Automatic liver tumor segmentation used the cascade multi-scale attention architecture method based on 3D U-Net | SpringerLink Automatic liver tumor segmentation used the cascade multi-scale attention architecture method based on 3D U-Net | SpringerLink](https://media.springernature.com/lw685/springer-static/image/art%3A10.1007%2Fs11548-022-02653-9/MediaObjects/11548_2022_2653_Fig6_HTML.jpg)
Automatic liver tumor segmentation used the cascade multi-scale attention architecture method based on 3D U-Net | SpringerLink
![Frontiers | Advanced Deep Learning Approach to Automatically Segment Malignant Tumors and Ablation Zone in the Liver With Contrast-Enhanced CT Frontiers | Advanced Deep Learning Approach to Automatically Segment Malignant Tumors and Ablation Zone in the Liver With Contrast-Enhanced CT](https://www.frontiersin.org/files/Articles/669437/fonc-11-669437-HTML/image_m/fonc-11-669437-g002.jpg)
Frontiers | Advanced Deep Learning Approach to Automatically Segment Malignant Tumors and Ablation Zone in the Liver With Contrast-Enhanced CT
LIT-PCBA: An Unbiased Data Set for Machine Learning and Virtual Screening | Journal of Chemical Information and Modeling
![Automatic liver tumor segmentation in CT with fully convolutional neural networks and object-based postprocessing | Scientific Reports Automatic liver tumor segmentation in CT with fully convolutional neural networks and object-based postprocessing | Scientific Reports](https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41598-018-33860-7/MediaObjects/41598_2018_33860_Fig3_HTML.png)