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Shape Detection of Liver From 2D Ultrasound Images
Applications of ultrasound images have expanded from fetal imaging to ab...
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Automatic Estimation of Fetal Abdominal Circumference from Ultrasound Images
Ultrasound diagnosis is routinely used in obstetrics and gynecology for ...
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Bone Feature Segmentation in Ultrasound Spine Image with Robustness to Speckle and Regular Occlusion Noise
3D ultrasound imaging shows great promise for scoliosis diagnosis thanks...
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Fast multi-scale edge-detection in medical ultrasound signals
In this article we suggest a fast multi-scale edge-detection scheme for ...
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Good and Bad Boundaries in Ultrasound Compounding: Preserving Anatomic Boundaries While Suppressing Artifacts
Ultrasound 3D compounding is important for volumetric reconstruction, bu...
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Weakly Supervised Context Encoder using DICOM metadata in Ultrasound Imaging
Modern deep learning algorithms geared towards clinical adaption rely on...
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Polyomino-Based Digital Halftoning
In this work, we present a new method for generating a threshold structu...
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A new ultrasound despeckling method through adaptive threshold
An efficient despeckling method using a quantum-inspired adaptive threshold function is presented for reducing noise of ultrasound images. In the first step, the ultrasound image is decorrelated by an spectrum equalization procedure due to the fact that speckle noise is neither Gaussian nor white. In fact, a linear filter is exploited to flatten the power spectral density (PSD) of the ultrasound image. Then, the proposed method shrinks complex wavelet coefficients based on the quantum-inspired adaptive threshold function. The proposed approach has been used to denoise both real and simulated data sets and compare with other widely adopted techniques. Experimental results demonstrate that the proposed method has a competitive performance to remove speckle noise and can preserve details and textures of medical ultrasound images.
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