1 citations · 2 across the 6 of their papers we have counts for
6 papers
UniPET: a universal network for high-quality PET image denoising across varied dose reduction factors
Zhiwen Yang, Yang Zhou, Haowei Chen +4
Most existing deep learning-based PET image denoising methods assume a fixed and known dose reduction factor (DRF) for low-dose PET images. However, these methods encounter signifi…
Rethinking Boundary Detection in Deep Learning-Based Medical Image Segmentation
Yi Lin, Dong Zhang, Xiao Fang +3
Medical image segmentation is a pivotal task within the realms of medical image analysis and computer vision. While current methods have shown promise in accurately segmenting majo…
Labeled-to-Unlabeled Distribution Alignment for Partially-Supervised Multi-Organ Medical Image Segmentation
Xixi Jiang, Dong Zhang, Xiang Li +3
Partially-supervised multi-organ medical image segmentation aims to develop a unified semantic segmentation model by utilizing multiple partially-labeled datasets, with each datase…
MedIAnomaly: A comparative study of anomaly detection in medical images
Yu Cai, Weiwen Zhang, Hao Chen +1
Anomaly detection (AD) aims at detecting abnormal samples that deviate from the expected normal patterns. Generally, it can be trained merely on normal data, without a requirement…
HMRNet: High and Multi-Resolution Network with Bidirectional Feature Calibration for Brain Structure Segmentation in Radiotherapy
Hao Fu, Guotai Wang, Wenhui Lei +5
Accurate segmentation of Anatomical brain Barriers to Cancer spread (ABCs) plays an important role for automatic delineation of Clinical Target Volume (CTV) of brain tumors in radi…
Contrastive Learning of Relative Position Regression for One-Shot Object Localization in 3D Medical Images
Wenhui Lei, Wei Xu, Ran Gu +3
Deep learning networks have shown promising performance for accurate object localization in medial images, but require large amount of annotated data for supervised training, which…