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20182022
most citedBrain segmentation based on multi-atlas guided 3D fully convolutional network ensembles

51 citations · 128 across the 22 of their papers we have counts for

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Showing 2022Show all

9 papers · 1 filter

eess.IV2022

DS3-Net: Difficulty-perceived Common-to-T1ce Semi-Supervised Multimodal MRI Synthesis Network

Ziqi Huang, Li Lin, Pujin Cheng +2

Contrast-enhanced T1 (T1ce) is one of the most essential magnetic resonance imaging (MRI) modalities for diagnosing and analyzing brain tumors, especially gliomas. In clinical prac…

eess.IV2022★ 1 cited

LesionPaste: One-Shot Anomaly Detection for Medical Images

Weikai Huang, Yijin Huang, Xiaoying Tang

Due to the high cost of manually annotating medical images, especially for large-scale datasets, anomaly detection has been explored through training models with only normal data.…

eess.IV2022★ 2 cited

Uni4Eye: Unified 2D and 3D Self-supervised Pre-training via Masked Image Modeling Transformer for Ophthalmic Image Classification

Zhiyuan Cai, Li Lin, Huaqing He +1

A large-scale labeled dataset is a key factor for the success of supervised deep learning in computer vision. However, a limited number of annotated data is very common, especially…

eess.IV2022★ 11 cited

Multi-modal Brain Tumor Segmentation via Missing Modality Synthesis and Modality-level Attention Fusion

Ziqi Huang, Li Lin, Pujin Cheng +2

Multi-modal magnetic resonance (MR) imaging provides great potential for diagnosing and analyzing brain gliomas. In clinical scenarios, common MR sequences such as T1, T2 and FLAIR…

eess.IV2022★ 1 cited

Student Becomes Decathlon Master in Retinal Vessel Segmentation via Dual-teacher Multi-target Domain Adaptation

Linkai Peng, Li Lin, Pujin Cheng +2

Unsupervised domain adaptation has been proposed recently to tackle the so-called domain shift between training data and test data with different distributions. However, most of th…

eess.IV2022★ 7 cited

JOINED : Prior Guided Multi-task Learning for Joint Optic Disc/Cup Segmentation and Fovea Detection

Huaqing He, Li Lin, Zhiyuan Cai +1

Fundus photography has been routinely used to document the presence and severity of various retinal degenerative diseases such as age-related macula degeneration, glaucoma, and dia…

cs.CV2022★ 3 cited

GAMMA Challenge:Glaucoma grAding from Multi-Modality imAges

Junde Wu, Huihui Fang, Fei Li +26

Color fundus photography and Optical Coherence Tomography (OCT) are the two most cost-effective tools for glaucoma screening. Both two modalities of images have prominent biomarker…

eess.IV2022

COROLLA: An Efficient Multi-Modality Fusion Framework with Supervised Contrastive Learning for Glaucoma Grading

Zhiyuan Cai, Li Lin, Huaqing He +1

Glaucoma is one of the ophthalmic diseases that may cause blindness, for which early detection and treatment are very important. Fundus images and optical coherence tomography (OCT…

eess.IV2022

Unsupervised Domain Adaptation for Cross-Modality Retinal Vessel Segmentation via Disentangling Representation Style Transfer and Collaborative Consistency Learning

Linkai Peng, Li Lin, Pujin Cheng +2

Various deep learning models have been developed to segment anatomical structures from medical images, but they typically have poor performance when tested on another target domain…