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Unsupervised speckle noise reduction technique for clinical ultrasound imaging [PDF]
UltrasonographyPurpose Deep learning–based image enhancement has significant potential in the field of ultrasound image processing, as it can accurately model complicated nonlinear artifacts and noise, such as ultrasonic speckle patterns.
Dongkyu Jung +4 more
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Remote Sensing, 2019 Synthetic aperture radar (SAR) images map Earth’s surface at high resolution, regardless of the weather conditions or sunshine phenomena. Therefore, SAR images have applications in various fields.
Hyunho Choi, Jechang Jeong
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Fast Speckle Noise Suppression Algorithm in Breast Ultrasound Image Using Three-Dimensional Deep Learning [PDF]
Frontiers in Physiology, 2022 The rapid development of ultrasound medical imaging technology has greatly broadened the scope of application of ultrasound, which has been widely used in the screening, diagnosis of breast diseases and so on.
Xiaofeng Li +3 more
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A novel algorithm for multiplicative speckle noise reduction in ex vivo human brain OCT images [PDF]
NeuroImage, 2022 Optical coherence tomography (OCT) images of ex vivo human brain tissue are corrupted by multiplicative speckle noise that degrades the contrast to noise ratio (CNR) of microstructural compartments.
Divya Varadarajan +5 more
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Non-Local Mean Denoising Algorithm Based on Fractional Compact Finite Difference Scheme Effectively Reduces Speckle Noise in Optical Coherence Tomography Images [PDF]
Micromachines, 2022 Optical coherence tomography (OCT) is used in various fields such, as medical diagnosis and material inspection, as a non-invasive and high-resolution optical imaging modality. However, an OCT image is damaged by speckle noise during its generation, thus
Huaiguang Chen, Jing Gao
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Physics-Informed Generative Adversarial Networks for Laser Speckle Noise Suppression [PDF]
SensorsIn high-resolution microscopic imaging, using shorter-wavelength ultraviolet (UV) lasers as illumination sources is a common approach. However, the high spatial coherence of such lasers, combined with the surface roughness of the sample, often introduces
Xiangji Guo +4 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Deep-learning-based on convolutional neural networks (CNN) has been widely applied in synthetic aperture radar (SAR) target recognition and made significant progress.
Yikui Zhai +8 more
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SSN2V: unsupervised OCT denoising using speckle split
Scientific Reports, 2023 Denoising in optical coherence tomography (OCT) is important to compensate the low signal-to-noise ratio originating from laser speckle. In recent years learning algorithms have been established as the most powerful denoising approach.
Julia Schottenhamml +6 more
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Open Computer Science, 2021 Ultrasonography is an extensively used medical imaging technique for multiple reasons. It works on the basic theory of echoes from the tissues under consideration.
Dilna Kaitheri Thacharedath +1 more
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Edge Enhancing Accelerated Diffusion Model for Speckle Denoising in Medical Imagery [PDF]
ITM Web of Conferences, 2019 Speckle noise occurs in a wide range of medical images due to sampling and digital degradation. Removing speckle noise from medical images is the key for further automated processing techniques like segmentation, and can help the clinicians with better ...
Bagchi Misra Arundhati +2 more
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