7 papers
Dynamic Dual-Feedback Conformal Inference for Time Series Forecasting
Songlin Du, Ling Luo, Uwe Aickelin
Quantifying uncertainty in time series forecasting is particularly demanding because sequential data exhibit temporal dependence and are prone to distributional changes. Conformal…
SUGFW+: An Uncertainty-guided Feature Weighting Framework for Cold Start Active Adaptation of SAM in Medical Image Segmentation
Xiaochuan Ma, Ning Zhu, Jia Fu +5
Cold Start Active Learning (CSAL) is important in improving the performance of a medical image segmentation model with low annotation budget by querying a small subset for annotati…
RAFM: Retrieval-Augmented Flow Matching for Unpaired CBCT-to-CT Translation
Xianhao Zhou, Jianghao Wu, Lanfeng Zhong +4
Cone-beam CT (CBCT) is routinely acquired in radiotherapy but suffers from severe artifacts and unreliable Hounsfield Unit (HU) values, limiting its direct use for dose calculation…
MetaSSL: A General Heterogeneous Loss for Semi-Supervised Medical Image Segmentation
Weiren Zhao, Lanfeng Zhong, Xin Liao +4
Semi-Supervised Learning (SSL) is important for reducing the annotation cost for medical image segmentation models. State-of-the-art SSL methods such as Mean Teacher, FixMatch and…
OpenPath: Open-Set Active Learning for Pathology Image Classification via Pre-trained Vision-Language Models
Lanfeng Zhong, Xin Liao, Shichuan Zhang +2
Pathology image classification plays a crucial role in accurate medical diagnosis and treatment planning. Training high-performance models for this task typically requires large-sc…
VLM-CPL: Consensus Pseudo Labels from Vision-Language Models for Annotation-Free Pathological Image Classification
Lanfeng Zhong, Zongyao Huang, Yang Liu +4
Classification of pathological images is the basis for automatic cancer diagnosis. Despite that deep learning methods have achieved remarkable performance, they heavily rely on lab…
Semi-supervised Pathological Image Segmentation via Cross Distillation of Multiple Attentions
Lanfeng Zhong, Xin Liao, Shaoting Zhang +1
Segmentation of pathological images is a crucial step for accurate cancer diagnosis. However, acquiring dense annotations of such images for training is labor-intensive and time-co…