Theoretical Framework to Predict Generalized Contrast-to-Noise Ratios of Photoacoustic Images With Applications to Computer Vision-Reference-Cited by-同舟云学术

Theoretical Framework to Predict Generalized Contrast-to-Noise Ratios of Photoacoustic Images With Applications to Computer Vision

Published:2022-06 Issue:6 Volume:69 Page:2098-2114
ISSN:0885-3010
Container-title:IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
language:
Short-container-title:IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

Author:

Gubbi Mardava R.¹^ORCID,Gonzalez Eduardo A.¹^ORCID,Bell Muyinatu A. Lediju²^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA

2. Department of Electrical and Computer Engineering, the Department of Computer Science, and the Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA

Funder

National Science Foundation

NSF SCH

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Acoustics and Ultrasonics,Instrumentation

Link

https://ieeexplore.ieee.org/ielam/58/9782472/9761193-aam.pdf

Reference47 articles.

1. On the LambertW function

2. Deep Learning-Based Photoacoustic Visual Servoing: Using Outputs from Raw Sensor Data as Inputs to a Robot Controller

3. A beamformer-independent method to predict photoacoustic visual servoing system failure from a single image frame

4. A method to estimate the spatial coherence of photoacoustic channel data without access to channel data

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