Richard G Abramson

Latest

• 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