HRLB Lab
HRLB Lab
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Shunxing Bao
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A cross-platform informatics system for the Gut Cell Atlas: integrating clinical, anatomical and histological data
Attention-Guided Supervised Contrastive Learning for Semantic Segmentation
Body Part Regression With Self-Supervision
CaCL: Class-Aware Codebook Learning for Weakly Supervised Segmentation on Diffuse Image Patterns
Compound Figure Separation of Biomedical Images with Side Loss
Construction of a multi-phase contrast computed tomography kidney atlas
Development and characterization of a chest CT atlas
High-resolution 3D abdominal segmentation with random patch network fusion
Pancreas CT Segmentation by Predictive Phenotyping
Phase identification for dynamic CT enhancements with generative adversarial network
Random Multi-Channel Image Synthesis for Multiplexed Immunofluorescence Imaging
Rap-Net: Coarse-To-Fine Multi-Organ Segmentation With Single Random Anatomical Prior
Renal cortex, medulla and pelvicaliceal system segmentation on arterial phase CT images with random patch-based networks
Semantic-Aware Contrastive Learning for Multi-object Medical Image Segmentation
Validation and estimation of spleen volume via computer-assisted segmentation on clinically acquired CT scans
Development and Characterization of a Chest CT Atlas
Learning from dispersed manual annotations with an optimized data weighting policy
Multi-Contrast Computed Tomography Healthy Kidney Atlas
Multi-Contrast Computed Tomography Healthy Kidney Atlas
Multi-path xD recurrent neural networks for collaborative image classification
Prediction of Type II Diabetes Onset with Computed Tomography and Electronic Medical Records
Time-distanced gates in long short-term memory networks
3D whole brain segmentation using spatially localized atlas network tiles
Cortical surface parcellation using spherical convolutional neural networks
Distanced LSTM: time-distanced gates in long short-term memory models for lung cancer detection
Stochastic tissue window normalization of deep learning on computed tomography
Adversarial synthesis learning enables segmentation without target modality ground truth
Fully convolutional neural networks improve abdominal organ segmentation
Splenomegaly segmentation using global convolutional kernels and conditional generative adversarial networks
Synseg-net: Synthetic segmentation without target modality ground truth
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