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2020 Index IEEE Transactions on Image Processing Vol. 29

2020 IEEE Transactions on Image Processing  
., +, 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  
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]

Maithra Raghu, Eric Schmidt
2020 arXiv   pre-print
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]

Xin Yi, Ekta Walia, Paul Babyn
2019 arXiv   pre-print
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  
., +, 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

Binh Thanh Kieu, Inigo Jauregi Unanue, Son Bao Pham, Hieu Xuan Phan, Massimo Piccardi
2021 2020 25th International Conference on Pattern Recognition (ICPR)  
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)  
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  
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]

Thien Huynh-The and Quoc-Viet Pham and Xuan-Qui Pham and Thanh Thi Nguyen and Zhu Han and Dong-Seong Kim
2022 arXiv   pre-print
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  
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

Hiba Ramadan, Chaymae Lachqar, Hamid Tairi
2020 Computational Visual Media  
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]

Asmat Zahra, Nazia Perwaiz, Muhammad Shahzad, Muhammad Moazam Fraz
2022 arXiv   pre-print
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

Qiulin Tang, Beshan Chiang, Akinola Akinyemi, Alexander Zamyatin, Bibo Shi, Satoru Nakanishi, Bruce R. Whiting, Christoph Hoeschen
2014 Medical Imaging 2014: Physics of Medical Imaging  
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  
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

Xingping Zhang, Yanchun Zhang, Guijuan Zhang, Xingting Qiu, Wenjun Tan, Xiaoxia Yin, Liefa Liao
2022 Frontiers in Oncology  
(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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