Comparison of Images Produced by Diffuse Optical Tomography with Two Different Backscatter Techniques

Int J Imaging Syst Tech

Canpolat

2021

Self Cite

The continuous-wave back reflection diffuse optical tomography (rCWDOT) system is one of the new medical imaging modalities. This study examines the success of reconstruction and three-dimensional (3D) image processing algorithms on data obtained from a heterogonous breast phantom by rCWDOT. Breast phantoms were prepared by putting a bit of spleen inside the tail. The spleen mimics a breast tumor since it has more blood than tail fat. rCWDOT was used to acquire data from the breast phantoms. The breast phantoms were reconstructed using the transpose-free quasi-minimal residual (TFQMR) reconstruction algorithm. Then, image processing algorithms were performed to improve the image quality. In image processing, 3D Gaussian filtering and bi-cubic interpolation were used to enhance the appearance and remove noise from the images. After the image processing, the images were evaluated numerically using the peak signal-to-noise ratio (PSNR) method. It has been shown that the used reconstruction technique and image processing algorithms for a heterogeneous breast phantom provided 3D images that resemble actual ones. This study will help researchers use the most convenient reconstruction algorithm and image processing algorithms and perform preclinical experiments in this field.

Section: Resultsmentioning

confidence: 99%

Approaches to preclinical studies with heterogeneous breast phantom using reconstruction and three‐dimensional image processing algorithms for diffuse optical imaging

Üncü

Int J Imaging Syst Tech

Canpolat

2021

Self Cite

“…However, CG-typed reconstruction methods are proven to be the most effective iterative method to find a solution of large, sparse, non-Hermitian, positive definite linear systems in CW-DOT systems. [16][17][18][19]36 In our previous study, we used Algebraic Reconstruction (ART), Simultaneous Iterative Reconstruction (SIRT), Truncated Singular Value Decomposition (TSVD), and Truncated Conjugate Gradient (TCG) techniques and compared them with each other. 17,18 In the study, we inferred that the TCG technique provides better images for our CW-DOT systems in line with the literature.…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, the BiCG was improved to solve the non-Hermitian system. 33 The BiCG uses the same subspaces with CG but another subspace defined in Equation (17), which is orthogonal to the P i subspace.…”

Section: Bi-conjugate Gradientmentioning

confidence: 99%

Image reconstruction for diffuse optical tomography using bi‐conjugate gradient and transpose‐free quasi minimal residual algorithms and comparison of them

Int J Imaging Syst Tech

Üncü

Merçan

et al. 2021

Self Cite

Diffuse optical tomography (DOT) is a new emerging modality in the diagnosis of soft tissue abnormalities. DOT image quality substantially depends on the reconstruction stage. In the literature, there are many reconstruction algorithms used in DOT systems. However, some algorithms were improved for solving specific cases but still need to be improved. The bi-conjugate gradient (BiCG) enhanced is one of the conjugate gradient (CG)-based reconstruction techniques for non-Hermitian systems. The BiCG provides a solution to a non-Hermitian system. However, it has erratic convergence in some cases. Therefore, DOT images reconstructed by BiCG can be at the wrong location and is inaccurate in some cases. In this study, we used continuous-wave diffuse optical tomography (CW-DOT) to acquire measurements from breast tissue phantoms with single or double inclusion at different depths and center-to-center separations and we have used the transpose free quasi minimal residual (TFQMR) reconstruction algorithm, improved as an alternative to BiCG for the first time in the CW-DOT system. Moreover, we have experimentally proved that TFQMR is superior to BiCG in some specific cases for the first time in CW-DOT. Therefore, we concluded that TFQMR has the potential to be able to be used in the reconstruction stage in CW-DOT.

“…In the literature, the CG technique is commonly used as one the most powerful technique to solve large, sparse, positive definite linear systems. The CG provides a solution to Hermitian systems [21], but not non-Hermitian matrix systems [8], [9]. For this case, some algorithms were developed to a proper solution system [9], [19].…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Difüz Optik Tomografi’de Modellenmiş Meme Tümörü Benzeri Dokuların Teşhisi için Simülasyon Deneyleriyle Geri Çatım Algoritmalarının Uygulanması

Düzce Üniversitesi Bilim Ve Teknoloji Dergisi

Üncü²,

Canpolat³

2021

Self Cite

In Diffuse Optical Tomography (DOT), data processing and reconstruction stages are crucial to obtain high-quality images. Thus, choosing suitable algorithms for the system is a critical choice. This study aims to determine an appropriate reconstruction algorithm for DOT imaging. There are several reconstruction algorithms used in DOT systems. Some algorithms have been improved for solving specific cases, and some still need to be improved. In this study, we used three algorithms for the reconstruction process: Singular Value Decomposition (SVD), Bi-Conjugated Gradient (Bi-CG), and Transpose Free Quasi Minimal Residual (TFQMR). In testing the algorithms, data of the simulation experiments have been used. The simulation experiments model the tumoral tissue within the breast. All three algorithms were produced correct images while the tumor close to the surface. In the case of the tumor that is not close to the breast surface, the tumor location on the images created by Bi-CG and SVD algorithms was not its actual location. However, the tumor location in the image created by the TFQMR algorithm was close to its actual location. Outcomes of the reconstruction algorithms were evaluated based on correctly defining the location of the tumors by using Mean Percentage Error (MPE), Mean Squared Error (MSE), and Mean Absolute Error (MAE) metrics. We have demonstrated the TFQMR algorithm is a more appropriate reconstruction technique for DOT systems. Thus, we have concluded that TFQMR can have the potential to be used in medical imaging systems.