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Image captioning applied to biomedical images can assist and accelerate the diagnosis process followed by clinicians.
Long short-term memory
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U-Net: Convolutional networks for biomedical image segmentation
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An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition
G. Tsatsaronis, G. Balikas, P. Malakasiotis, I. Partalas, M. Zschunke, M. R. Alvers, D. Weissenborn, A. Krithara, S. Petridis, D. Polychronopoulos, et al. 2015 · 2015
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CIDEr: Consensus-based image description evaluation
R. Vedantam, Z. C. L. Zitnick, and D. Parikh. 2015 · 2015
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O. Vinyals, A. Toshev, S. Bengio, and D. Erhan. 2015 · 2015
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Convolutional neural network for reconstruction of 7T-like images from 3T MRI using appearance and anatomical features
NLM at ImageCLEF 2017 caption task
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Automatic detection and classification of regions of FDG uptake in whole-body PET-CT lymphoma studies
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Overview of ImageCLEFcaption 2017 - Image caption prediction and concept extraction tasks to understand biomedical images
C. Eickhoff, I. Schwall, A. García Seco de Herrera, and H. Müller. 2017 · 2017
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alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
K. Bahrami, F. Shi, I. Rekik, and D. Shen. 2016 · 2016
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Automatic detection of cerebral microbleeds from MR images via 3D convolutional neural networks
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun. 2016 · 2016
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Re-evaluating automatic metrics for image captioning
M. Kilickaya, A. Erdem, N. Ikizler-Cinbis, and E. Erdem. 2016 · 2016
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Medical image captioning: Learning to describe medical image findings using multi-task-loss CNN
P. Kisilev, E. Sason, E. Barkan, and S. Hashoul. 2016 · 2016
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Generating binary tags for fast medical image retrieval based on convolutional nets and radon transform
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A CNN regression approach for real-time 2D/3D registration
S. Miao, Z. J. Wang, and R. Liao. 2016 · 2016
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J.-G. Lee, S. Jun, Y.-W. Cho, H. Lee, G. B. Kim, J. B. Seo, and N. Kim. 2017 · 2017
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ISIA at the ImageCLEF 2017 image caption task
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CheXNet: Radiologist-level pneumonia detection on chestX-rays with deep learning
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Producing radiologist-quality reports for interpretable artificial intelligence
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Overview of the ImageCLEF 2018 caption prediction tasks
A. García Seco de Herrera, C. Eickhoff, V. Andrearczyk, and H. Müller. 2018 · 2018
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On the automatic generation of medical imaging reports
B. Jing, P. Xie, and E. Xing. 2018 · 2018
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A cross modal deep learning based approach for caption prediction and concept detection by CS Morgan State
Md M. Rahman. 2018 · 2018
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Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists
P. Rajpurkar, J. Irvin, R. L. Ball, K. Zhu, B. Yang, H. Mehta, et al. 2018 · 2018
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UMass at ImageCLEF caption prediction 2018 task
Y. Su, F. Liu, and M. P. Rosen. 2018 · 2018
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TieNet: Text-image embedding network for common thorax disease classification and reporting in chest X-rays
X. Wang, Y. Peng, L. Lu, Z. Lu, and R. M. Summers. 2018 · 2018
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ImageSem at ImageCLEF 2018 caption task: Image retrieval and transfer learning
Y. Zhang, X. Wang, Z. Guo, and J. Li. 2018 · 2018
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Show, attend and tell: Neural image caption generation with visual attention
K. Xu, J. Ba, R. Kiros, K. Cho, A. Courville, R. Salakhudinov, R. Zemel, and Y. Bengio. 2015 · 2057
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ChestX-ray8: Hospital-scale chest X-ray database and benchmarks on weakly-supervised classification and localization of common thorax diseases
X. Wang, Y. Peng, L. Lu, Z. Lu, M. Bagheri, and R. M. Summers. 2017 · 2097
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