activity
20192023
most citedHarvesting, Detecting, and Characterizing Liver Lesions from Large-scale Multi-phase CT Data via Deep Dynamic Texture Learning

9 citations · 43 across the 15 of their papers we have counts for

collaborators
Showing cs.CVShow all

15 papers · 1 filter

cs.CV2023

SLPT: Selective Labeling Meets Prompt Tuning on Label-Limited Lesion Segmentation

Fan Bai, Ke Yan, Xiaoyu Bai +6

Medical image analysis using deep learning is often challenged by limited labeled data and high annotation costs. Fine-tuning the entire network in label-limited scenarios can lead…

cs.CV20232 cited

Anatomy-Aware Lymph Node Detection in Chest CT using Implicit Station Stratification

Ke Yan, Dakai Jin, Dazhou Guo +5

Finding abnormal lymph nodes in radiological images is highly important for various medical tasks such as cancer metastasis staging and radiotherapy planning. Lymph nodes (LNs) are…

cs.CV2023

Matching in the Wild: Learning Anatomical Embeddings for Multi-Modality Images

Xiaoyu Bai, Fan Bai, Xiaofei Huo +10

Radiotherapists require accurate registration of MR/CT images to effectively use information from both modalities. In a typical registration pipeline, rigid or affine transformatio…

cs.CV2023

SAMConvex: Fast Discrete Optimization for CT Registration using Self-supervised Anatomical Embedding and Correlation Pyramid

Zi Li, Lin Tian, Tony C. W. Mok +8

Estimating displacement vector field via a cost volume computed in the feature space has shown great success in image registration, but it suffers excessive computation burdens. Mo…

cs.CV20232 cited

Devil is in the Queries: Advancing Mask Transformers for Real-world Medical Image Segmentation and Out-of-Distribution Localization

Mingze Yuan, Yingda Xia, Hexin Dong +13

Real-world medical image segmentation has tremendous long-tailed complexity of objects, among which tail conditions correlate with relatively rare diseases and are clinically signi…

cs.CV2021

Learning from Subjective Ratings Using Auto-Decoded Deep Latent Embeddings

Bowen Li, Xinping Ren, Ke Yan +6

Depending on the application, radiological diagnoses can be associated with high inter- and intra-rater variabilities. Most computer-aided diagnosis (CAD) solutions treat such data…