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2020 Index IEEE Transactions on Image Processing Vol. 29
2020
IEEE Transactions on Image Processing
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., +, TIP 2020 2702-2713 High-Resolution Encoder-Decoder Networks for Low-Contrast Medical Image Segmentation. ...
., +, TIP 2020 1915-1928
Self-Supervised Feature Augmentation for Large Image Object Detection.
Pan, X., +, TIP 2020 6745-6758
Semantic Image Segmentation by Scale-Adaptive Networks. ...
doi:10.1109/tip.2020.3046056
fatcat:24m6k2elprf2nfmucbjzhvzk3m
Table of contents
2020
IEEE Transactions on Image Processing
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Cuadra 7751 Magnetic Resonance Imaging High-Resolution Encoder-Decoder Networks for Low-Contrast Medical Image Segmentation ............................ ................................................ ...
Cha, and J.-H. Han 303 Segmenting Cellular Retinal Images by Optimizing Super-Pixels, Multi-Level Modularity, and Cell Boundary Representation ..................................................... O. ...
Lin, and Zhang, Y. Tian, K. Wang, W. Zhang, and F.- ...
doi:10.1109/tip.2019.2940373
fatcat:i7hktzn4wrfz5dhq7hj75u6esa
A Survey of Deep Learning for Scientific Discovery
[article]
2020
arXiv
pre-print
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Over the past few years, we have seen fundamental breakthroughs in core problems in machine learning, largely driven by advances in deep neural networks. ...
by the community. ...
Guy Gur-Ari for feedback and comments on earlier versions. ...
arXiv:2003.11755v1
fatcat:igy35ko5hfcj5ctp5nck7y2z44
Generative Adversarial Network in Medical Imaging: A Review
[article]
2019
arXiv
pre-print
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These properties have attracted researchers in the medical imaging community, and we have seen rapid adoption in many traditional and novel applications, such as image reconstruction, segmentation, detection ...
interested in this technique. ...
This model has achieved state-of-the-art performance in many image generation tasks, including text-to-image synthesis , super-resolution , and image-to-image translation (Zhu et al., 2017a) . ...
arXiv:1809.07294v3
fatcat:5j5i6shlcvbbjm74ceidzg6rc4
2020 Index IEEE Transactions on Visualization and Computer Graphics Vol. 26
2021
IEEE Transactions on Visualization and Computer Graphics
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., +, TVCG Jan. 2020 949-959 DeepOrganNet: On-the-Fly Reconstruction and Visualization of 3D / 4D Lung Models from Single-View Projections by Deep Deformation Network. ...
Medical image processing CerebroVis: Designing an Abstract yet Spatially Contextualized Cerebral Artery Network Visualization. ...
., and Ando, R., Simulating Liquids on Dynamically Warping Grids; TVCG June 2020 2288-2302 Igarashi, T., see Ibayashi, H., 2288-2302 Isaacs, K., see Williams, K., 1118-1128 Isenberg, P., see Chang, R ...
doi:10.1109/tvcg.2021.3111804
fatcat:lvhpoz5sqjhclo3roocrdtzs2m
Learning Neural Textual Representations for Citation Recommendation
2021
2020 25th International Conference on Pattern Recognition (ICPR)
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Super Resolution by
Widening and Deepening
DAY 2 -Jan 13, 2021
Tang, Hui; Wang, Bin; Zhou, Jun;
Gao, Yongsheng
810
DE-Net: Dilated Encoder Network for Automated Tongue
Segmentation
DAY 2 - ...
DAY 2 -Jan 13, 2021
Lan, Sheng; Guo, Zhenhua
47
A Joint Super-Resolution and Deformable Registration Network for
3D Brain Images
DAY 2 -Jan 13, 2021
Matsumi, Susumu; Yamada,
Keiichi
54
Few-Shot ...
doi:10.1109/icpr48806.2021.9412725
fatcat:3vge2tpd2zf7jcv5btcixnaikm
Table of Contents
2019
2019 IEEE/CVF International Conference on Computer Vision (ICCV)
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USA) ByteDance AI Lab), Yuchen Fan (University of Illinois at Urbana-Champaign), and Ning Xu (Adobe Research) Self-Supervised Difference Detection for Weakly-Supervised Semantic Segmentation 5207 Wataru ...
College London)
Few-Shot Generalization for Single-Image 3D Reconstruction via Priors
3817
Bram Wallace (Cornell University) and Bharath Hariharan (Cornell
University)
Digging Into Self-Supervised ...
doi:10.1109/iccv.2019.00004
fatcat:5aouo4scprc75c7zetsimylj2y
CARS 2021: Computer Assisted Radiology and Surgery Proceedings of the 35th International Congress and Exhibition Munich, Germany, June 21–25, 2021
2021
International Journal of Computer Assisted Radiology and Surgery
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Acknowledgements This work has been funded by the research project PI18/00169 from Instituto de Salud Carlos III & FEDER funds. ...
obtained by using our previous self-supervised 3D-GAN EC scheme (Figure 2b ). ...
At present, the clinical biopsy of tumors is generally performed by free-hand under image-guidance. ...
doi:10.1007/s11548-021-02375-4
pmid:34085172
fatcat:6d564hsv2fbybkhw4wvc7uuxcy
Artificial Intelligence for the Metaverse: A Survey
[article]
2022
arXiv
pre-print
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In this context, metaverse, a term formed by combining meta and universe, has been introduced as a shared virtual world that is fueled by many emerging technologies, such as fifth-generation networks and ...
We first deliver a preliminary of AI, including machine learning algorithms and deep learning architectures, and its role in the metaverse. ...
In [76] , a fully CNN for image super-resolution was proposed with a lightweight structure, which can learn an end-to-end relation between input low-resolution images and output high-resolution images ...
arXiv:2202.10336v1
fatcat:35isd745dbaqfnpzthnmbaosue
Survey on Generative Adversarial Behavior in Artificial Neural Tasks
2022
Iraqi Journal for Computer Science and Mathematics
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GANs can use learned representations for a variety of applications, including image synthesis, semantic imaging, style transfer, super magnification, and segmentation. ...
GANs implicitly distribute complex and high-resolution images, sounds, and data. ...
[15] described a Super-Resolution Generative Adversarial Networks (SRGAN) that takes a low-resolution image as input and generates a high-resolution image with 4x up-scaling to boost pixel density. ...
doi:10.52866/ijcsm.2022.02.01.009
fatcat:mfqgweniwzc5pl4oony3vzoh2y
A survey of recent interactive image segmentation methods
2020
Computational Visual Media
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Image segmentation is one of the most basic tasks in computer vision and remains an initial step of many applications. ...
In this paper, we focus on interactive image segmentation (IIS), often referred to as foreground-background separation or object extraction, guided by user interaction. ...
Another supervised ACM based on self-organizing-map (SOM) is presented in Ref. [126] . ...
doi:10.1007/s41095-020-0177-5
fatcat:n6njrwuohjg6tgvapz2m4hecvi
Person Re-identification: A Retrospective on Domain Specific Open Challenges and Future Trends
[article]
2022
arXiv
pre-print
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Owing to its potential in various applications and research significance, a plethora of deep learning based re-Id approaches have been proposed in the recent years. ...
In this context, a comprehensive review of current re-ID approaches in solving theses challenges is needed to analyze and focus on particular aspects for further advancements. ...
In [209] issue of no availability of super resolution images was challenged. ...
arXiv:2202.13121v1
fatcat:luwwbcwspndqpauj4dosmmojee
A combined local and global motion estimation and compensation method for cardiac CT
2014
Medical Imaging 2014: Physics of Medical Imaging
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The Dt and FOM values were lower from the images reconstructed by the AIDR 3D in comparison with the FBP technique. ...
of anatomical variation in the statistical atlas) and make use of an alternative prior derived from a patch driven search of the atlas data. ...
We report a label-free (i.e. no chemical de-waxing, or staining) method of imaging large pieces of prostate tissue (typically 1 cm ? ...
doi:10.1117/12.2043492
fatcat:fyzpc5m6jbh7fjohqpdmtzkhte
CARS 2020—Computer Assisted Radiology and Surgery Proceedings of the 34th International Congress and Exhibition, Munich, Germany, June 23–27, 2020
2020
International Journal of Computer Assisted Radiology and Surgery
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stimulate complimentary thoughts and actions within the given domain of discourse by all parties involved in the scientific/medical communication process". ...
the exchange/communication of R&D ideas by means of verbal and written statements made by responsible authors, scrutinized by informed reviewers and utilized by an open-minded audience, with the aim to ...
Acknowledgments This work was partly supported by a grant from Galgo Medical SL. We thank NVIDIA for the Titan X hardware grant that allowed us to process the images in a faster way. ...
doi:10.1007/s11548-020-02171-6
pmid:32514840
fatcat:lyhdb2zfpjcqbf4mmbunddwroq
Deep Learning With Radiomics for Disease Diagnosis and Treatment: Challenges and Potential
2022
Frontiers in Oncology
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(medical big data and multitype data and expert knowledge in medical), limitations of data-driven processes (reproducibility and interpretability of studies, different treatment alternatives for various ...
In addition, deep learning-based techniques for automatic segmentation and radiomic analysis are being analyzed to address limitations such as rigorous workflow, manual/semi-automatic lesion annotation ...
Any automated segmentation technique that acts as an outlining tool should undergo careful review and approval of the results by medical experts to ensure the reliability of the study. ...
doi:10.3389/fonc.2022.773840
pmid:35251962
pmcid:PMC8891653
fatcat:3h5tnm3aznb33k5ylkcd6tvs4e
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