21 citations · 45 across the 12 of their papers we have counts for
7 papers · 1 filter
International Multi-Centre Validation of Unsupervised Domain Adaptation for Precise Discrimination between Normal and Abnormal Retinal Development
Zhanhan Tu, Nikhil Reddy, Helen J. Kuht +27
Arrested retinal development can cause childhood visual impairment, but grading optical coherence tomography scans is difficult to standardise across devices and centres. We develo…
ClinReadNet: A clinical reading-inspired network for low-dose abdominal CT image quality assessment
Xianye Xiao, Yulong Zou, Yujie Luo +6
In abdominal CT imaging, developing a low-dose, no-reference image quality assessment (No-reference IQA) model that mimics doctors' reading habits for evaluating CT image quality h…
MGML: A Plug-and-Play Meta-Guided Multi-Modal Learning Framework for Incomplete Multimodal Brain Tumor Segmentation
Yulong Zou, Bo Liu, Cun-Jing Zheng +6
Leveraging multimodal information from Magnetic Resonance Imaging (MRI) plays a vital role in lesion segmentation, especially for brain tumors. However, in clinical practice, multi…
ERANet: Edge Replacement Augmentation for Semi-Supervised Meniscus Segmentation with Prototype Consistency Alignment and Conditional Self-Training
Siyue Li, Yongcheng Yao, Junru Zhong +9
Manual segmentation is labor-intensive, and automatic segmentation remains challenging due to the inherent variability in meniscal morphology, partial volume effects, and low contr…
Review of AlexNet for Medical Image Classification
Wenhao Tang, Junding Sun, Shuihua Wang +1
In recent years, the rapid development of deep learning has led to a wide range of applications in the field of medical image classification. The variants of neural network models…
EAFP-Med: An Efficient Adaptive Feature Processing Module Based on Prompts for Medical Image Detection
Xiang Li, Long Lan, Husam Lahza +5
In the face of rapid advances in medical imaging, cross-domain adaptive medical image detection is challenging due to the differences in lesion representations across various medic…
Weakly Supervised Semantic Segmentation in 3D Graph-Structured Point Clouds of Wild Scenes
Haiyan Wang, Xuejian Rong, Liang Yang +3
The deficiency of 3D segmentation labels is one of the main obstacles to effective point cloud segmentation, especially for scenes in the wild with varieties of different objects.…