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Corrigendum to Äcceleration of spleen segmentation with end-to-end deep learning method and automated pipeline" Comput. Biol. Med. 107 (2019) 109-117.

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Generalizing Deep Whole Brain Segmentation for Pediatric and Post-Contrast MRI with Augmented Transfer Learning., , , , , , , , and . CoRR, (2019)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)Towards Portable Large-Scale Image Processing with High-Performance Computing., , , , , , , , , and 5 other author(s). J. Digital Imaging, 31 (3): 304-314 (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)SynSeg-Net: Synthetic Segmentation Without Target Modality Ground Truth., , , , , , , , and . CoRR, (2018)Enabling Multi-Shell b-Value Generalizability of Data-Driven Diffusion Models with Deep SHORE., , , , , , , , , and 2 other author(s). CoRR, (2019)Reproducibility evaluation of SLANT whole brain segmentation across clinical magnetic resonance imaging protocols., , , , , and . Medical Imaging: Image Processing, volume 10949 of SPIE Proceedings, page 109492V. SPIE, (2019)Montage based 3D medical image retrieval from traumatic brain injury cohort using deep convolutional neural network., , , , , and . Medical Imaging: Image Processing, volume 10949 of SPIE Proceedings, page 109492U. SPIE, (2019)Technology Enablers for Big Data, Multi-Stage Analysis in Medical Image Processing., , , , , , , , , and 1 other author(s). BigData, page 1337-1346. IEEE, (2018)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)