Liver and Liver Tumor Segmentation | Kaggle
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Effective Data Storytelling for Larger-Than-Memory Datasets with Streamlit, Dask, and Coiled
How to Explore your Object Detection Dataset With Streamlit
The scans in Liver Tumor Segmentation Challenge (LiTS) 2017 dataset and... | Download Scientific Diagram
Liver segmentation results based on RA-UNet-II. (a) is from the LiTS... | Download Scientific Diagram
The WORC database: MRI and CT scans, segmentations, and clinical labels for 930 patients from six radiomics studies | medRxiv
Frontiers | Advanced Deep Learning Approach to Automatically Segment Malignant Tumors and Ablation Zone in the Liver With Contrast-Enhanced CT
LiTS – Liver Tumor Segmentation Challenge (LiTS17) - Academic Torrents
The Liver Tumor Segmentation Benchmark (LiTS) - ScienceDirect
E $$^2$$ Net: An Edge Enhanced Network for Accurate Liver and Tumor Segmentation on CT Scans | SpringerLink
Automatic liver tumor segmentation in CT with fully convolutional neural networks and object-based postprocessing | Scientific Reports
LiTS – Liver Tumor Segmentation Challenge (LiTS17) - Academic Torrents
CodaLab - Competition
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
LIT-DATASET
CT-ORG, a new dataset for multiple organ segmentation in computed tomography | Scientific Data
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
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
The Liver Tumor Segmentation Benchmark (LiTS) - ScienceDirect
GitHub - Confusezius/unet-lits-2d-pipeline: Liver Lesion Segmentation with 2D Unets
A study of generalization and compatibility performance of 3D U-Net segmentation on multiple heterogeneous liver CT datasets | BMC Medical Imaging | Full Text
LiTS17 Dataset | Papers With Code
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
