Search Results for author:
Found 7 papers, 3 papers with code
Intermediate Domain-guided Adaptation for Unsupervised Chorioallantoic Membrane Vessel Segmentation
Moreover, research on CAM vessel segmentation algorithms remains limited, and the lack of public datasets contributes to poor prediction performance.
Label-free Prediction of Vascular Connectivity in Perfused Microvascular Networks in vitro
To address this issue, a Vessel Connectivity Network (VC-Net) was developed for label-free assessment of vascular connectivity.
MCPA: Multi-scale Cross Perceptron Attention Network for 2D Medical Image Segmentation
The Cross Perceptron first captures the local correlations using multiple Multi-scale Cross Perceptron modules, facilitating the fusion of features across scales.
Phased Progressive Learning with Coupling-Regulation-Imbalance Loss for Imbalanced Data Classification
This loss is effective in addressing quantity imbalances and outliers, while regulating the focus of attention on samples with varying classification difficulties.
An explainable two-dimensional single model deep learning approach for Alzheimer's disease diagnosis and brain atrophy localization
In this research, we propose a novel end-to-end deep learning approach for automated diagnosis of AD and localization of important brain regions related to the disease from sMRI data.
Single Model Deep Learning on Imbalanced Small Datasets for Skin Lesion Classification
This paper proposes a novel single-model based strategy for classification of skin lesions on small and imbalanced datasets.
Low-cost and high-performance data augmentation for deep-learning-based skin lesion classification
At the network search stage, the DCNNs are fine-tuned with the full training set in order to select the model with the highest BACC.
