Learning Transferability in Deep Segmentation of Liver Metastases
Author:
Affiliation:
1. LaTIM UMR 1101, Inserm,Brest,France
Funder
Ligue Contre le Cancer
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10635099/10635102/10635479.pdf?arnumber=10635479
Reference13 articles.
1. Validity of RECIST Version 1.1 for Response Assessment in Metastatic Cancer: A Prospective, Multireader Study
2. Hepatic metastasis from colorectal cancer
3. Scale-adaptive supervoxel-based random forests for liver tumor segmentation in dynamic contrast-enhanced CT scans
4. Current and Emerging Trends in Medical Image Segmentation With Deep Learning
5. Multi-modal medical Transformers: A meta-analysis for medical image segmentation in oncology
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