Results 21 to 30 of about 10,352,216 (337)
SwinIR: Image Restoration Using Swin Transformer [PDF]
2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 2021 Image restoration is a long-standing low-level vision problem that aims to restore high-quality images from low-quality images (e.g., downscaled, noisy and compressed images).
Jingyun Liang +5 more
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Frontiers in Medicine, 2023 Background and purposeColorectal cancer is a common fatal malignancy, the fourth most common cancer in men, and the third most common cancer in women worldwide.
Liyu Shi +18 more
doaj +1 more source
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising [PDF]
IEEE Transactions on Image Processing, 2016 The discriminative model learning for image denoising has been recently attracting considerable attentions due to its favorable denoising performance.
K. Zhang +4 more
semanticscholar +1 more source
BMC Cardiovascular Disorders, 2023 Background This study aimed to investigate the correlation between the high-risk characteristics of high-resolution MRI carotid vulnerable plaques and the clinical risk factors and concomitant acute cerebral infarction (ACI).
Yongxiang Tang +11 more
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Retinal Imaging and Image Analysis [PDF]
IEEE Reviews in Biomedical Engineering, 2010 Many important eye diseases as well as systemic diseases manifest themselves in the retina. While a number of other anatomical structures contribute to the process of vision, this review focuses on retinal imaging and image analysis. Following a brief overview of the most prevalent causes of blindness in the industrialized world that includes age ...
Abramoff, M.D. +2 more
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Hypercomplex Image- to- Image Translation
2022 International Joint Conference on Neural Networks (IJCNN), 2022 Image-to-image translation (I2I) aims at transferring the content representation from an input domain to an output one, bouncing along different target domains. Recent I2I generative models, which gain outstanding results in this task, comprise a set of diverse deep networks each with tens of million parameters.
Eleonora Grassucci +3 more
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V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation [PDF]
International Conference on 3D Vision, 2016 Convolutional Neural Networks (CNNs) have been recently employed to solve problems from both the computer vision and medical image analysis fields. Despite their popularity, most approaches are only able to process 2D images while most medical data used ...
F. Milletarì +2 more
semanticscholar +1 more source
Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations [PDF]
International Journal of Computer Vision, 2016 Despite progress in perceptual tasks such as image classification, computers still perform poorly on cognitive tasks such as image description and question answering.
Ranjay Krishna +11 more
semanticscholar +1 more source
ImageJ2: ImageJ for the next generation of scientific image data [PDF]
BMC Bioinformatics, 2017 ImageJ is an image analysis program extensively used in the biological sciences and beyond. Due to its ease of use, recordable macro language, and extensible plug-in architecture, ImageJ enjoys contributions from non-programmers, amateur programmers, and
C. Rueden +6 more
semanticscholar +1 more source
Imaging Biomarkers or Biomarker Imaging? [PDF]
Pharmaceuticals, 2014 Since biomarker imaging is traditionally understood as imaging of molecular probes, we highly recommend to avoid any confusion with the previously defined term “imaging biomarkers” and, therefore, only use “molecular probe imaging (MPI)” in that context. Molecular probes (MPs) comprise all kinds of molecules administered to an organism which inherently
Markus Mitterhauser, Wolfgang Wadsak
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