output
20192025
most citedAnnotation-efficient deep learning for automatic medical image segmentation

313 citations

7 papers

cs.CV2025

Paired Image Generation with Diffusion-Guided Diffusion Models

Haoxuan Zhang, Wenju Cui, Yuzhu Cao +4

The segmentation of mass lesions in digital breast tomosynthesis (DBT) images is very significant for the early screening of breast cancer. However, the high-density breast tissue…

eess.IV2023★ 10 cited

Progressive Dual Priori Network for Generalized Breast Tumor Segmentation

Li Wang, Lihui Wang, Zixiang Kuai +4

To promote the generalization ability of breast tumor segmentation models, as well as to improve the segmentation performance for breast tumors with smaller size, low-contrast and…

eess.IV2022★ 125 cited

2D and 3D CT Radiomic Features Performance Comparison in Characterization of Gastric Cancer: A Multi-center Study

Lingwei Meng, Di Dong, Xin Chen +5

Objective: Radiomics, an emerging tool for medical image analysis, is potential towards precisely characterizing gastric cancer (GC). Whether using one-slice 2D annotation or whole…

eess.IV2020★ 313 cited

Annotation-efficient deep learning for automatic medical image segmentation

Shanshan Wang, Cheng Li, Rongpin Wang +12

Automatic medical image segmentation plays a critical role in scientific research and medical care. Existing high-performance deep learning methods typically rely on large training…

eess.IV2020★ 83 cited

A coarse-to-fine framework for unsupervised multi-contrast MR image deformable registration with dual consistency constraint

Weijian Huang, Hao Yang, Xinfeng Liu +5

Multi-contrast magnetic resonance (MR) image registration is useful in the clinic to achieve fast and accurate imaging-based disease diagnosis and treatment planning. Nevertheless,…

q-bio.QM2019★ 39 cited

Systematic external evaluation of published population pharmacokinetic models for tacrolimus in adult liver transplant recipients

Xiaojun Cai, Ruidong Li, Changcheng Sheng +8

Background:Diverse tacrolimus population pharmacokinetic models in adult liver transplant recipients have been established to describe the PK characteristics of tacrolimus in the l…

eess.IV2019★ 77 cited

CLCI-Net: Cross-Level fusion and Context Inference Networks for Lesion Segmentation of Chronic Stroke

Hao Yang, Weijian Huang, Kehan Qi +5

Segmenting stroke lesions from T1-weighted MR images is of great value for large-scale stroke rehabilitation neuroimaging analyses. Nevertheless, there are great challenges with th…