5 citations · 5 across the 2 of their papers we have counts for
2 papers
cs.CV2024★ 5 cited
Predictive Accuracy-Based Active Learning for Medical Image Segmentation
Jun Shi, Shulan Ruan, Ziqi Zhu +4
Active learning is considered a viable solution to alleviate the contradiction between the high dependency of deep learning-based segmentation methods on annotated data and the exp…
eess.IV2023
H-DenseFormer: An Efficient Hybrid Densely Connected Transformer for Multimodal Tumor Segmentation
Jun Shi, Hongyu Kan, Shulan Ruan +6
Recently, deep learning methods have been widely used for tumor segmentation of multimodal medical images with promising results. However, most existing methods are limited by insu…