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Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
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Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
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When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
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Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
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Reducing Line Loss

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X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging
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Speckle Reduction Using Adaptive Receive-Side Compounding.

Are Charles Jensen, Andreas Austeng

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    Adaptive steering mitigates spatial resolution loss in coherent imaging caused by receive compounding. This technique improves image quality by reducing smearing and enhancing structure depiction, offering a practical solution for clearer imaging.

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    Area of Science:

    • Coherent imaging systems
    • Medical ultrasound
    • Signal processing

    Background:

    • Speckle reduction in coherent imaging typically involves averaging images with different speckle realizations.
    • Receive compounding, using varied transducer-array element weights, reduces speckle but degrades spatial resolution.
    • This degradation manifests as image artifacts like smearing and expansion of image regions.

    Purpose of the Study:

    • To investigate methods for mitigating the negative effects of receive compounding in coherent imaging.
    • To evaluate the combination of receive compounding with adaptive array steering.
    • To assess the impact of this combined approach on spatial resolution and image fidelity.

    Main Methods:

    • Receive compounding using different transducer-array element weights.
    • Adaptive steering based on a minimum-output distortionless response criterion (akin to Capon beamformer).
    • Application and evaluation on simulated (Field II), phantom, and in vivo ultrasound data.

    Main Results:

    • Adaptive steering positively impacted all studied receive compounding techniques, mitigating unwanted effects.
    • The Thomson's multitaper method combined with adaptive steering outperformed non-compounded imaging in structure geometry reproduction.
    • While speckle reduction was slightly lower and spatial speckle patterns changed subtly, the benefits were deemed tolerable.

    Conclusions:

    • Combining adaptive steering with receive compounding effectively mitigates resolution loss and image artifacts.
    • The proposed method offers an intuitive and easily implementable approach to enhance coherent imaging quality.
    • This technique shows promise for improving diagnostic accuracy in ultrasound applications.