PUMA

academical publication management
collect, organize, and share publications

( en | de )

 

Disambiguation of "Abramson, Richard G."

Author of the publication

copydeleteadd this publication to your clipboard
Evaluation of Six Registration Methods for the Human Abdomen on Clinically Acquired CT.

, , , , , , , and . IEEE Trans. Biomed. Engineering, 63 (8): 1563-1572 (2016)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

G. Daiß

G. Wagner

Richard Völker University of Stuttgart

Univ. -Prof. Dr. Richard Dipper University of Stuttgart

Richard Powers University of Stuttgart

 

Other publications of authors with the same name

Fully convolutional neural networks improve abdominal organ segmentation., , , , , , , , , and 1 other author(s). Medical Imaging: Image Processing, volume 10574 of SPIE Proceedings, page 105742V. SPIE, (2018)Efficient abdominal segmentation on clinically acquired CT with SIMPLE context learning., , , , , , and . Medical Imaging: Image Processing, volume 9413 of SPIE Proceedings, page 94130L. SPIE, (2015)Splenomegaly Segmentation on Multi-modal MRI using Deep Convolutional Networks., , , , , , , , , and 1 other author(s). CoRR, (2018)Adversarial Synthesis Learning Enables Segmentation Without Target Modality Ground Truth., , , , , and . CoRR, (2017)Whole abdominal wall segmentation using Augmented Active Shape Models (AASM) with multi-atlas label fusion and level set., , , , and . Medical Imaging: Image Processing, volume 9784 of SPIE Proceedings, page 97840U. SPIE, (2016)Multi-atlas segmentation enables robust multi-contrast MRI spleen segmentation for splenomegaly., , , , , , and . Medical Imaging: Image Processing, volume 10133 of SPIE Proceedings, page 101330A. SPIE, (2017)SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth., , , , , , , , and . CoRR, (2018)Splenomegaly Segmentation on Multi-Modal MRI Using Deep Convolutional Networks., , , , , , , , , and 1 other author(s). IEEE Trans. Med. Imaging, 38 (5): 1185-1196 (2019)Semi-Supervised Multi-Organ Segmentation through Quality Assurance Supervision., , , , , , , , , and 2 other author(s). CoRR, (2019)Corrigendum to Äcceleration of spleen segmentation with end-to-end deep learning method and automated pipeline" Comput. Biol. Med. 107 (2019) 109-117., , , , , , , and . Comput. Biol. Medicine, (2022)