Dual consistency assisted multi-confident learning for the hepatic vessel segmentation using noisy labels
Nam Phuong Nguyen (VinBrain),* Tuan Van Vo (VinBrain), Soan T. M. Duong (Le Quy Don Technical University), Chanh D Tr Nguyen (VinBrain), Trung Bui (Individual), QUOC HUNG TRUONG (VINBRAIN)
The 33rd British Machine Vision Conference
Abstract
Noisy hepatic vessel labels from Computer Tomography (CT) are popular due to vessels' low-contrast and complex morphology. This is challenging for automatic hepatic vessel segmentation, which is essential to many hepatic surgeries such as liver resection and transplantation. To exploit the noisy labeled data, we proposed a novel semi-supervised framework called dual consistency assisted multi-confident learning (DC-Multi-CL) for automatic hepatic vessel segmentation. The proposed framework contains a dual consistency architecture that learns not only the high-quality annotation data but also the low-quality data by boosting the prediction consistency on low-quality labeled data robustly. Furthermore, we also present a multi-confident learning component to exploit the capability of global context information from multi-level network features and eradicate the human efforts on refining the low-quality data. Combining these ideas, we believe that it raises a potentially valuable approach to handle segmentation task, especially when the annotation data are noisy, e.g. unlabeled and mislabeled voxel-wise. Extensive experiments on two public datasets, i.e. 3DIRCADb and MSD8, demonstrate the effectiveness of each component and the superiority of the proposed method to other state-of-the-art methods in hepatic vessel segmentation and semi-supervised segmentation.Video
Citation
@inproceedings{Nguyen_2022_BMVC,
author = {Nam Phuong Nguyen and Tuan Van Vo and Soan T. M. Duong and Chanh D Tr Nguyen and Trung Bui and QUOC HUNG TRUONG},
title = {Dual consistency assisted multi-confident learning for the hepatic vessel segmentation using noisy labels},
booktitle = {33rd British Machine Vision Conference 2022, {BMVC} 2022, London, UK, November 21-24, 2022},
publisher = {{BMVA} Press},
year = {2022},
url = {https://bmvc2022.mpi-inf.mpg.de/0725.pdf}
}
Copyright © 2022
The British Machine Vision Conference is organised by