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-to-noise 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.