An Application of Simulated Annealing in Compensation of Nonlinearity of Scanners

Manwar, Rayyan; Zafar, Mohsin; Podoleanu, Adrian G.H.; Avanaki, Kamran

doi:10.3390/app9081655

Cited by 7 publications

(6 citation statements)

References 37 publications

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“…With regards to optimization, utilizing optimization methods such as the simulated annealing algorithm or Genetic algorithm along with an effective cost function will allow an automated and more effective calibration [60,[75][76][77][78][79][80][81].…”

Section: Discussionmentioning

confidence: 99%

Development of a Stationary 3D Photoacoustic Imaging System Using Sparse Single-Element Transducers: Phantom Study

et al. 2019

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Photoacoustic imaging (PAI) is an emerging label-free and non-invasive modality for imaging biological tissues. PAI has been implemented in different configurations, one of which is photoacoustic computed tomography (PACT) with a potential wide range of applications, including brain and breast imaging. Hemispherical Array PACT (HA-PACT) is a variation of PACT that has solved the limited detection-view problem. Here, we designed an HA-PACT system consisting of 50 single element transducers. For implementation, we initially performed a simulation study, with parameters close to those in practice, to determine the relationship between the number of transducers and the quality of the reconstructed image. We then used the greatest number of transducers possible on the hemisphere and imaged copper wire phantoms coated with a light absorbing material to evaluate the performance of the system. Several practical issues such as light illumination, arrangement of the transducers, and an image reconstruction algorithm have been comprehensively studied.

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Section: Discussionmentioning

confidence: 99%

Development of a Stationary 3D Photoacoustic Imaging System Using Sparse Single-Element Transducers: Phantom Study

et al. 2019

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“…In our study, we aim to clean the signal through our proposed E-net architecture, and these signals are further used to reconstruct the images. Rat brain is places in the circular PAM system [17], and Nd: YAG laser is used to acquire the low and high energy signal pairs. In figure 1(b), a detailed diagram of experimental setup has been show with the scanning area [18].…”

Section: Materials and Methodology Experimental Setupmentioning

confidence: 99%

E-Unet: a deep learning method for photoacoustic signal enhancement

Aggrawal¹,

Zafar²,

Islam³

et al. 2023

Photons Plus Ultrasound: Imaging and Sensing 2023

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We developed a deep learning algorithm, called enhancement Unet (E-Unet), to improve the signal-to-noise ratio (SNR) of signals acquired in a photoacoustic computed microscopy (PAM) system. We tried various combination of custom loss functions which included peak-amplitude, peak-position and mean-squared signal value with Adam optimizer for training purposes. For the testing purposes, we acquired PAM data with complicated phantoms in biological tissue. The performance of the improved signals is evaluated in terms of SNR, structural similarity index (SSIM), root mean square error (RMSE) and Pearson correlation

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“…Simulated annealing (SA) [31] is a searching algorithm mainly designed for global optimization problems [32].…”

Section: Simulated Annealingmentioning

confidence: 99%

“…Recently, Manwar et al [32] used an algorithm similar to simulated annealing to reduce the nonlinearity of Galvo scanners. In that study, they evaluated the algorithm in different frequencies to synthesize the signal.…”

Section: Simulated Annealingmentioning

confidence: 99%

A Novel Bio-Inspired Method for Early Diagnosis of Breast Cancer through Mammographic Image Analysis

et al. 2019

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Breast cancer is a current problem that causes the death of many women. In this work, we test meta-heuristics applied to the segmentation of mammographic images. Traditionally, the application of these algorithms has a direct relationship with optimization problems; however, in this study, its implementation is oriented to the segmentation of mammograms using the Dunn index as an optimization function, and the grey levels to represent each individual. The update of grey levels during the process results in the maximization of the Dunn's index function; the higher the index, the better the segmentation will be. The results showed a lower error rate using these meta-heuristics for segmentation compared to a well-adopted classical approach known as the Otsu method.

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An Application of Simulated Annealing in Compensation of Nonlinearity of Scanners

Cited by 7 publications

References 37 publications

Development of a Stationary 3D Photoacoustic Imaging System Using Sparse Single-Element Transducers: Phantom Study

Development of a Stationary 3D Photoacoustic Imaging System Using Sparse Single-Element Transducers: Phantom Study

E-Unet: a deep learning method for photoacoustic signal enhancement

A Novel Bio-Inspired Method for Early Diagnosis of Breast Cancer through Mammographic Image Analysis

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