HRLB Lab
HRLB Lab
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Richard G Abramson
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Corrigendum to\" Acceleration of spleen segmentation with end-to-end deep learning method and automated pipeline\"[Comput. Biol. Med. 107 (2019) 109-117].
High-resolution 3D abdominal segmentation with random patch network fusion
Rap-Net: Coarse-To-Fine Multi-Organ Segmentation With Single Random Anatomical Prior
Validation and estimation of spleen volume via computer-assisted segmentation on clinically acquired CT scans
Learning from dispersed manual annotations with an optimized data weighting policy
Outlier guided optimization of abdominal segmentation
Semi-supervised multi-organ segmentation through quality assurance supervision
Validation and Optimization of Multi-Organ Segmentation on Clinical Imaging Archives
Validation and optimization of multi-organ segmentation on clinical imaging archives
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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