The Monte Carlo (MC) method is a computer simulation that is widely used in different disciplines including physics, biology, biophysics, medical imaging, biomedical engineering, etc. In addition, MC method is often used to simulate the interaction of radiation with cells, tissues, and the environment. In the present study, mass attenuation coefficient, stopping power, and penetrating distance calculations were performed for cell membranes having an approximately 60-100Å thickness. These calculations have been done for lipid bilayer structure of cell membrane via MC techniques employing two of the most known computer-aided calculation and simulation software which are MC methods such as SRIM-2013 (The Stopping and Range of Ions in Matter) and MCNPv6 (Monte Carlo N-Particle) with XCOM software. Stopping power and penetrating distance calculations were obtained using SRIM-2013. Also, both XCOM software and MCNPv6 simulation code were used to obtain photon interaction parameters within the energy range of 0.01 – 10000keV. Obtained all results from different codes have been visualized by graphing for evaluation.

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.

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 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.

Difüz Optik Tomografi (DOT) sistemleri optik medikal görüntüleme yöntemlerindendir. DOT sistemlerinin görüntü oluşturma aşaması oldukça önemlidir. Bu çalışma da DOT sisteminde kullanılan iteratif geri çatım algoritmaları için ideal iterasyon sayının literatürdeki metotlara alternatif bir metot ile belirlenebilmesi amaçlanmaktadır. Bu metodun, kontrast-gürültü oranı (Contrast to Noise Ratio, CNR) metoduna benzer bir çalışma prensibi vardır. Bu metodu test edebilmek için MATLAB programı ile simülasyon deneyleri yapılmıştır. Simülasyon verisi oluşturulduktan sonra CNR benzeri iterasyon belirleme algoritması kullanılarak belirlenen iterasyon sayısı ile geri çatım algoritmaları modellenen verinin görüntülerini oluşturmuştur. Bu çalışmada geliştirilen iterasyon belirleme algoritması Kesikli Eşlenik Gradyent (Truncated Conjugate Gradient, TCG), Çift Eşlenik Gradyent (Bi-Conjugate Gradient) ve Transpozu Olmadan Kısmen Minimum Rezidüel (Transpose Free Quasi Minimal Residual, TFQMR) algoritmalarına entegre edilmiştir.

In breast cancer diagnosis, tumoral and non‐tumoral breast lesions differentiation is a challenge. We investigate the feasibility of continuous‐wave back reflection diffuse optical tomography (rDOT) in differentiation tumoral and non‐tumoral breast lesions to solve this problem. Modified Beer–Lambert Law and Rytov solution of diffusion approximation of the radiative energy transfer equation were used together in a continuous wave rDOT system for the near‐infrared imaging the breast with a lesion. The rDOT data were acquired from 15 lesions in 12 patients with a palpable lump after standard clinical examination with mammography, magnetic resonance imaging (MRI), and ultrasonography (US). Also, the measurements symmetrically from the other breast's counterpart were used as a functional imaging base. Histopathological examination revealed the tumor distribution as five invasive ductal carcinomas, one lobular carcinoma, one sclerosing adenosis, and one papilloma. The remaining seven lesions (one hamartoma, one postoperative scar tissue, two cysts, two islands of fibroglandular tissue, and one mastitis) were classified as non‐tumoral breast lesions. They were diagnosed based on clinical, US, mammography, or MRI findings. Tumoral lesions presented a contrast in rDOT tomographic images, whereas non‐tumoral lesions such as hamartoma and cysts did not show any difference except mastitis. In mastitis cases, rDOT showed higher contrast similar to tumoral lesions. After antibiotic treatment, the mastitis area had no high contrast when compared with the healthy breast tissue. We have demonstrated that the rDOT system can differentiate between actual breast tumors from non‐tumoral breast lesions such as cyst, the island of fibroglandular tissue, or hamartoma.

Surekli Dalga Difuz Optik Tomografi (Continuous Wave Diffuse Optical Tomography, CWDOT) sistemi tip alaninda kullanilan goruntuleme sistemlerinden biridir. Bu calismanin amaci, CWDOT sistemi ile olusturulan uc boyutlu (3B) meme fantomu goruntulerine farkli goruntu isleme yontemlerini 3B olarak uygulamak ve en uygun goruntu isleme yontemini belirlemektir. Meme fantomu intralipid, su ve Indosiyanin yesili (ICG) karisiminda yapildi, tumoru temsil etmesi icin karisimin icine inkluzyonlar konuldu. Bu calismada, goruntu isleme algoritmalarinda uzaysal filtrelerden (spatial filter); Ortalama, Gauss, Laplas, Laplasyen Gauss filtreleme yontemleri uygulandi. Daha sonra, en yakin komsu, cift dogrusal, cift kubik ve kubik spline interpolasyon yontemleri goruntulere uygulandi. Goruntu isleme sonuclari; Tepe sinyalinin gurultuye orani (PSNR), Ortalama hata karesi (MSE) ve Yapisal benzerlik orani (SSIM) yontemleri kullanilarak sayisal karsilastirmalari yapilmistir. Bu calisma ile tumor benzeri yapilarin meme fantomu icindeki konumlarini gercek sekil ve boyutlarda en iyi ortaya cikaran goruntu isleme yontemleri belirlendi. CWDOT sistemine uygun olan goruntu isleme yontemlerinin Gauss filtreleme ve cift kubik interpolasyon yontemleri oldugu gosterildi.

Sürekli Dalga Difüz Optik Tomografi (Continuous Wave Diffuse Optical Tomography, CWDOT) sistemi tıp alanında kullanılan görüntüleme sistemlerinden biridir. Bu çalışmanın amacı, CWDOT sistemi ile oluşturulan üç boyutlu (3B) meme fantomu görüntülerine farklı görüntü işleme yöntemlerini 3B olarak uygulamak ve en uygun görüntü işleme yöntemini belirlemektir. Meme fantomu intralipid, su ve Indosiyanin yeşili (ICG) karışımında yapıldı, tümörü temsil etmesi için karışımın içine inklüzyonlar konuldu. Bu çalışmada, görüntü işleme algoritmalarında uzaysal filtrelerden (spatial filter); Ortalama, Gauss, Laplas, Laplasyen Gauss filtreleme yöntemleri uygulandı. Daha sonra, en yakın komşu, çift doğrusal, çift kübik ve kübik spline interpolasyon yöntemleri görüntülere uygulandı. Görüntü işleme sonuçları; Tepe sinyalinin gürültüye oranı (PSNR), Ortalama hata karesi (MSE) ve Yapısal benzerlik oranı (SSIM) yöntemleri kullanılarak sayısal karşılaştırmaları yapılmıştır. Bu çalışma ile tümör benzeri yapıların meme fantomu içindeki konumlarını gerçek şekil ve boyutlarda en iyi ortaya çıkaran görüntü işleme yöntemleri belirlendi. CWDOT sistemine uygun olan görüntü işleme yöntemlerinin Gauss filtreleme ve çift kübik interpolasyon yöntemleri olduğu gösterildi.

Diffuse optical tomography (DOT) utilizes wavelength range of 750-950 nm to map the spatial distribution of the tissue chromophores of breast tissue for cancer diagnosis or follow up prognosis. DOT allows tomographic reconstructions of tissue optical properties. Several reconstruction methods have been developed to minimize artifacts and obtain more realistic tomographic images. In order to compare four different reconstruction algorithms, data acquired from tissue phantoms using a DOT system. Algebraic reconstruction technique (ART), simultaneous iteration reconstruction technique (SIRT), truncated singular value decomposition (TSVD) and truncated conjugate gradient (TCG) techniques have been compared in terms of location of inclusion in the tissue phantoms. It has been shown that images reconstructed by the subspace techniques, TSVD and TCG locating the inclusion position better than the algebraic methods ART and SIRT. Beside, images reconstructed by TSVD and TCG have less artifact when compared to images of ART and SIRT.

Several methods are used in the early diagnosis of breast cancer. Due to the disadvantages of these methods, the diffuse optical tomography (DOT) system is one of new methods have been developed to support these methods. In the DOT, the reconstruction technique used to create image is very important. Each reconstruction technique has some disadvantages. Thus, it is important to create an image by using the appropriate technique for DOT system. In this study, we have combined two algorithms called Truncated Conjugate Gradient (TCG) and Transpose Free Quasi Minimal Residual (TFQMR) to create a new algorithm named TCG-TFQMR. The reason of combining the two algorithms is low resolution of TCG and slow running of TFQMR. The new algorithm is first tested using simulation data created by Matlab. Then, in-vitro experiments were performed by acquiring DOT data from a breast phantom. The both reconstruction algorithms TCG and TCG-TFQMR were used to reconstruct the tissue phantom. It has been shown that TCG-TFQMR algorithm has better resolution than TCG.

In recent years, breast cancers have been diagnosed by various imaging modalities. One of those imaging methods is Diffuse Optical Tomography (DOT). Currently, in imaging systems, image processing methods which is the next stage when digital images are obtained, are important task for the images to be well formed. This study was applied interpolation methods, one of the image processing methods to make the images better, to protect the details and also enlargement and resizing without distortion. In this study, we used three- dimensional (3D) images generated by measurements from breast phantom with the DOT system. Four interpolation methods; nearest neighbor interpolation, bilinear interpolation, bicubic interpolation and cubic spline interpolation are applied to the 3D images. The signal- tonoise ratios (SNR) were calculated to determine the quality of the images after the interpolation methods applied. In order to evaluate the images obtained from different directions and angles, two dimensional (2D) and three dimensional (3D) images were created and their advantages and disadvantages were compared. After interpolation methods were applied, signal- to- noise ratios (SNR) were compared and tested for compatibility with our system and it was determined that the most appropriate method was the cubic spline interpolation.

In recent years, breast cancers have been diagnosed by several imaging modalities. One of these imaging methods is the diffuse optical tomography (DOT) system. In the presented study, in-vitro data were acquired from a breast phantom using the our designed DOT system. Breast phantoms were reconstructed in three dimensions (3D) using Truncated Conjugate Gradient (TCG) reconstruction algorithm. Then, image processing methods were applied to the raw images. Image segmentation technique was used to distinguish between "object" and "backgrounds". Later, 3D Gaussian filtering was applied to smooth the image and reduce noise. Finally, a three dimensional interpolation was applied to the noise free images in order to obtain a more realistic 3D image of the tissue phantoms. Thus, we have modified most popular image processing methods to apply the DOT images. As a result, we obtained user friendly, fast, accurate and user independent images processing methods for the DOT systems.

Currently, there are several devices have been used for diagnosis of breast cancer such as X-ray tomography ultrasound and MRI. These devices sending harmful photons to the body, costly, lack of resolution and portability. Therefore searching new methods to diagnose breast cancer are necessity. One of these methods is Diffuse Optical Tomography (DOT). In DOT study, 808 nm wavelength laser which has a high penetration to tissue is used. In in-vitro experiments, DOT measurements were acquired from a breast phantom was mixture of water and 1% Intralipid. Indocyanine green (ICG) was added to the mixture to make absorption coefficient 0.04 cm -1 , similar to the breast tissue. A transparent balloon was filled Intralipid and ICG with absorption coefficient of 0.16 cm -1 to mimic tumor inclusion 3D Image of breast phantoms were created by using Algebraic Reconstruction Technique (ART) and Truncated Conjugate Gradient (TCG) methods. The results obtained by the TCG algorithm are closer to the real, which is the closest of inclusion's dimensions and contains less artifact. The system which we use consists of 2401 measurement and 2250 voxels so it is called as over-determined systems. According to findings, we inference that TCG algorithm works better than ART for over-determined system.