Published in ISBI 2022 (Poster), 2022
This work proposes a Combined-Learning Network (CLNet) consisting of a classification network, a segmentation network and a feature fusion module for segmentation and classification of skin lesion.
Recommended citation: coming soon coming soon
Published in ISBI 2022 (Oral), 2022
This work introduces a multi-scale context-guided network with coarse-to-fine localization and classification, named CCF-Net, for lumbar spine disease identification.
Recommended citation: Chen, ZiFan, et al. "Multi-Scale Context-Guided Lumbar Spine Disease Identification with Coarse-to-fine Localization and Classification." arXiv preprint arXiv:2203.08408 (2022). https://ieeexplore.ieee.org/document/9761528
Published in arXiv, 2021
This work proposes composite localization framework for human pose estimation by dividing the complex learning objective into two simpler ones.
Recommended citation: Chen, ZiFan, et al. "Composite Localization for Human Pose Estimation." arXiv preprint arXiv:2105.07245 (2021). https://arxiv.org/pdf/2105.07245.pdf
Published in ECR 2021 (Oral), 2021
To develop a deep learning model on 3D CT images to generate the volumetric segmentation of a gastric tumor from the annotation of its largest cross-section.
Recommended citation: Chen, ZiFan, et al. "Slice-propagated 3D Gastric Tumour Segmentation From A Single 2D Annotation." European Congress of Radiology (ECR) 2021. https://connect.myesr.org/course/ai-in-abdominal-imaging/