90 citations · 96 across the 7 of their papers we have counts for
7 papers
LiMT: A Multi-task Liver Image Benchmark Dataset
Zhe Liu, Kai Han, Siqi Ma +10
Computer-aided diagnosis (CAD) technology can assist clinicians in evaluating liver lesions and intervening with treatment in time. Although CAD technology has advanced in recent y…
Frequency Domain Unlocks New Perspectives for Abdominal Medical Image Segmentation
Kai Han, Siqi Ma, Chengxuan Qian +4
Accurate segmentation of tumors and adjacent normal tissues in medical images is essential for surgical planning and tumor staging. Although foundation models generally perform wel…
CLIMD: A Curriculum Learning Framework for Imbalanced Multimodal Diagnosis
Kai Han, Chongwen Lyu, Lele Ma +5
Clinicians usually combine information from multiple sources to achieve the most accurate diagnosis, and this has sparked increasing interest in leveraging multimodal deep learning…
Adaptive Label Correction for Robust Medical Image Segmentation with Noisy Labels
Chengxuan Qian, Kai Han, Jianxia Ding +4
Deep learning has shown remarkable success in medical image analysis, but its reliance on large volumes of high-quality labeled data limits its applicability. While noisy labeled d…
Visual Agents as Fast and Slow Thinkers
Guangyan Sun, Mingyu Jin, Zhenting Wang +7
Achieving human-level intelligence requires refining cognitive distinctions between System 1 and System 2 thinking. While contemporary AI, driven by large language models, demonstr…
TransFlow: Transformer as Flow Learner
Yawen Lu, Qifan Wang, Siqi Ma +4
Optical flow is an indispensable building block for various important computer vision tasks, including motion estimation, object tracking, and disparity measurement. In this work,…
Solve the Puzzle of Instance Segmentation in Videos: A Weakly Supervised Framework with Spatio-Temporal Collaboration
Liqi Yan, Qifan Wang, Siqi Ma +2
Instance segmentation in videos, which aims to segment and track multiple objects in video frames, has garnered a flurry of research attention in recent years. In this paper, we pr…