Comparison of noise reduction methods in photoacoustic microscopy.

Photoacoustic microscopy (PAM) is classified as a hybrid imaging technique based on the photoacoustic effect and has been frequently studied in recent years. Photoacoustic (PA) signals are inherently recorded in a noisy environment and are also exposed to noise by system components. Therefore, it is essential to reduce the noise in PA signals to reconstruct images with less error. In this study, an image reconstruction algorithm for PAM system was implemented and different filtering approaches for denoising were compared. Studies were carried out in three steps: simulation, experimental phantom and blood cell studies. FIR low-pass and band-pass filters and Discrete Wavelet Transform (DWT) based filters (mother wavelets: "bior3.5″, "bior3.7″, "sym7″) with four different thresholding techniques were examined. For the evaluation purposes, Root Mean Square Error (RMSE), Signal to Noise Ratio (SNR) and Contrast to Noise Ratio (CNR) metrics were calculated. In the simulation studies, the most effective methods were obtained as: sym7/heursure/hard thresh. combination (low and medium level noise) and bior3.7/sqtwolog/soft thresh. combination (high-level noise). In experimental phantom studies, noise was classified into five levels. Different filtering approaches perform better depending on the SNR of PA images. For the blood cell study, based on the standard deviation in the background, sym7/sqtwolog/soft thresh. combination provided the best improvement and this result supported the experimental phantom results.

Investigation of grid performance using simple image quality tests.

Antiscatter grids improve the X-ray image contrast at a cost of patient radiation doses. The choice of appropriate grid or its removal requires a good knowledge of grid characteristics, especially for pediatric digital imaging. The aim of this work is to understand the relation between grid performance parameters and some numerical image quality metrics for digital radiological examinations. The grid parameters such as bucky factor (BF), selectivity (Σ), Contrast improvement factor (CIF), and signal-to-noise improvement factor (SIF) were determined following the measurements of primary, scatter, and total radiations with a digital fluoroscopic system for the thicknesses of 5, 10, 15, 20, and 25 cm polymethyl methacrylate blocks at the tube voltages of 70, 90, and 120 kVp. Image contrast for low- and high-contrast objects and high-contrast spatial resolution were measured with simple phantoms using the same scatter thicknesses and tube voltages. BF and SIF values were also calculated from the images obtained with and without grids. The correlation coefficients between BF values obtained using two approaches (grid parameters and image quality metrics) were in good agreement. Proposed approach provides a quick and practical way of estimating grid performance for different digital fluoroscopic examinations.

Fourier transform magnetic resonance current density imaging (FT-MRCDI) from one component of magnetic flux density.

Fourier transform (FT)-based algorithms for magnetic resonance current density imaging (MRCDI) from one component of magnetic flux density have been developed for 2D and 3D problems. For 2D problems, where current is confined to the xy-plane and z-component of the magnetic flux density is measured also on the xy-plane inside the object, an iterative FT-MRCDI algorithm is developed by which both the current distribution inside the object and the z-component of the magnetic flux density on the xy-plane outside the object are reconstructed. The method is applied to simulated as well as actual data from phantoms. The effect of measurement error on the spatial resolution of the current density reconstruction is also investigated. For 3D objects an iterative FT-based algorithm is developed whereby the projected current is reconstructed on any slice using as data the Laplacian of the z-component of magnetic flux density measured for that slice. In an injected current MRCDI scenario, the current is not divergence free on the boundary of the object. The method developed in this study also handles this situation.

A simulation study of the variability of indocyanine green kinetics and using structural a priori information in dynamic contrast enhanced diffuse optical tomography (DCE-DOT).

We investigated (1) the variability of indocyanine green kinetics (ICG) between different cases in the existence of random noise, changing the size of the imaging region, the location and the size of the inclusion, (2) the use of structural a priori information to reduce the variability. We performed two-dimensional simulation studies for this purpose. In the simulations, we used a two-compartmental model to describe the ICG transport and obtained pharmacokinetic parameters. The transfer constant and the rate constant showed a wide variation, i.e. 60% and 95%, respectively, when random Gaussian noise with a standard deviation of 1% in amplitude and 0.4 degrees in phase was added to data. Moreover, recovered peak ICG concentration and time to reach the peak concentration was different within different cases. When structural a priori information was used in the reconstructions, the variations in the transfer and the rate constant were reduced to 29%, 15%, respectively. As a result, although the recovered peak concentration was still case dependent, the variability of the shape of the kinetic curve was reduced.

Simultaneous in vivo dynamic magnetic resonance-diffuse optical tomography for small animal imaging.

We present simultaneous measurement of enhancement kinetics of an optical and a magnetic resonance (MR) contrast agent in a small animal breast tumor model (R3230 ac) using a combined MR-diffuse optical tomographic (MR-DOT) imaging system. A mixture of a small molecular-weight MR contrast agent gadolinium-diethylene-triamine-pentaacetic acid (Gd-DTPA) and a large molecular-weight optical contrast agent indocyanine green (ICG) was administered intravenously for multimodal dynamic imaging. Coregistration of optical and MR images was accomplished using agar-water-based markers. Using T(2) and dynamic T(1) weighted MR images, we divided the entire tumor into two regions of interest (ROI): a viable and a nonviable region. The absorption enhancements in the ROIs were calculated. An enhancement of the ICG was observed in the viable region. On the contrary, there was a lower enhancement in the nonviable region.

Diffuse optical tomographic reconstruction using multifrequency data.

We investigated the use of multifrequency diffuse optical tomography (MF-DOT) data for the reconstruction of the optical parameters. The experiments were performed in a 63 mm diameter cylindrical phantom containing a 15 mm diameter cylindrical object. Modulation frequencies ranging from 110 MHz to 280 MHz were used in the phantom experiments changing the contrast in absorption of the object with respect to the phantom while keeping the scattering value the same. The diffusion equation was solved using the finite element method. The sensitivity information from each frequency was combined to form a single Jacobian. The inverse problem was solved iteratively by minimizing the difference between the measurements and forward problem using single and multiple modulation frequency data. A multiparameter Tikhonov scheme was used for regularization. The phantom results show that the peak absorption coefficient in a region of interest was obtained with an error less then 5% using two-frequency reconstruction for absorption contrast values up to 2.2 times higher than background and 10% for the absorption contrast values larger than 2.2. The use of two-frequency data is sufficient to improve the quantitative accuracy compared with the single frequency reconstruction with appropriate selection of these frequencies.

Contrast and spatial resolution in MREIT using low amplitude current.

Magnetic resonance-electrical impedance tomography employs low amplitude currents injected or induced inside an object. The additional magnetic field due to these currents results in a phase in the MR images. In this study, a modified fast spin-echo sequence was used to measure this magnetic field, which is obtained by scaling the MR phase image. A finite element method with first order triangular elements was used for the solution of the forward problem. An iterated sensitivity matrix-based algorithm was developed for the inverse problem. The resulting ill-conditioned matrix equation was regularized using the Tikhonov method and solved using a conjugate gradient solver. The spatial and contrast resolution of the technique was tested using agarose gel phantoms. A circular phantom with 7 cm diameter and 1 cm thickness is used in the phantom experiments. The amplitude of the injected current was 1 mA. 3, 5 and 8 mm diameter insulators and high conductor objects are used for the spatial resolution study and an average full-width half-maximum value of 4.7 mm is achieved for the 3 mm insulator case. For the contrast analysis, the conductivity of a 15 mm object is varied between 44% and 500% with respect to the background and results are compared to the ideal reconstruction.

Combined diffuse optical tomography (DOT) and MRI system for cancer imaging in small animals.

Recently, there has been a great amount of interest in developing multi-modality imaging techniques for oncologic research and clinical studies with the aim of obtaining complementary information and, thus, improving the detection and characterization of tumors. In this present work, the details of a combined MR-diffuse optical imaging system for dual-modality imaging of small animals are given. As a part of this effort, a multi-spectral frequency domain diffuse optical tomography system is integrated with an MRI system. Here, a network analyzer provides the rf modulation signal for the laser diodes and measures the amplitude and the phase of the detected signals. Photomultiplier tubes are utilized to measure low-level signals. The integration of this optical imaging system with the 4T MRI system is realized by incorporating a fiber adaptive interface inside the MR magnet. Coregistration is achieved by a special probe design utilizing fiducial markers. A finite element algorithm is used to solve the diffusion equation and an inverse solver based on this forward solver is implemented to calculate the absorption and scattering maps from the acquired data. The MR a priori information is used to guide the optical reconstruction algorithm. Phantom studies show that the absorption coefficient of a 7 mm inclusion in an irregular object located in 64 mm phantom is recovered with 11% error when MR a priori information is used. ENU induced tumor model is used to test the performance of the system in vivo.

In vivo MRI electrical impedance tomography (MREIT) of tumors.

A significant increase in electrical conductivity of neoplasticities compared to healthy tissues and benign formations has been reported in several studies. We previously reported preliminary results with MR based Electrical Impedance Tomography (MREIT) on several phantoms and a single animal. In the presented study, we applied the technique on ten tumor-bearing rats and collected MREIT images to investigate the potential of MREIT for characterizing malignant tumors. Results show that the tumors had significantly higher mean conductivity compared to the mean of conductivity in the rest of the body. Although heterogeneity of conductivity was observed in the tumor, the mean was still higher than the background.

Measurement of ion diffusion using magnetic resonance electrical impedance tomography.

In magnetic resonance electrical impedance tomography (MREIT), currents are applied to an object, the resulting magnetic flux density measured using MRI and the conductivity distribution reconstructed using these MRI data. In this study, we assess the ability of MREIT to monitor changes in the conductivity distribution of an agarose gel phantom, using injected current pulses of 900 microA. The phantom initially contained a distinct region of high sodium chloride concentration which diffused into the background over time. MREIT data were collected over a 12 h span, and conductivity images were reconstructed using the iterative sensitivity matrix method with Tikhonov regularization. The results indicate that MREIT was able to monitor the changing conductivity and concentration distributions resulting from the diffusion of ions within the agarose gel phantom.

Design and implementation of a multifrequency near-infrared diffuse optical tomography system.

The design and implementation of a multifrequency and multispectral diffuse optical tomography system is described. Four wavelengths are utilized: 665, 785, 808, and 830 nm. The system is based on a network analyzer, which provides rf modulation signals for the laser diodes, as well as measures the amplitude and the phase of the detected signals. Six different modulation frequencies ranging from 110 to 280 MHz are used. The details of instrumentation, calibration, data acquisition, and performance of the system are given. A finite element algorithm is used to solve the diffusion equation, and an inverse solver based on this forward solver is implemented to calculate the absorption and scattering maps from the acquired data. Data acquisition for one wavelength is completed in less than 2.5 min for a single modulation frequency. The measurement repeatability is 0.5% in ac intensity and 0.2 deg in phase. The performance of the system is evaluated with phantom studies. A multifrequency reconstruction algorithm is used, in which a single absorption and scattering image pair is obtained using the whole dataset obtained at different modulation frequencies. It is shown that the multifrequency reconstruction approach provides superior image quality compared to the single frequency counterpart.

Resolution and contrast in magnetic resonance electrical impedance tomography (MREIT) and its application to cancer imaging.

It has been reported that the electrical impedance of malignancies could be 20-40 times lower than healthy tissues and benign formations. Therefore, in vivo impedance imaging of suspicious lesions may prove to be helpful in improving the sensitivity and specificity of detecting malignant tumors. Several systems have been developed to map the conductivity distribution inside a volume of tissue, however they suffer from poor spatial resolution because the measurements are taken only from surface electrodes. MRI based impedance imaging (MREIT) is a novel method, in which weak electrical currents are injected into the tissue and the resulting perturbations in the magnetic field are measured using MRI. This method has been shown to provide better resolution compared to previous techniques of impedance imaging because the measurements are taken from inside the object on a uniform grid. Thus, it has the potential to be a useful modality that may detect malignancies earlier. Several phantom imaging experiments were performed to investigate the spatial resolution and dynamic range of contrast of this technique. The method was also applied to a live rat bearing a R3230 AC tumor. Tumor location was identified by contrast enhanced imaging.

Experimental results for 2D magnetic resonance electrical impedance tomography (MR-EIT) using magnetic flux density in one direction.

Magnetic resonance electrical impedance tomography (MR-EIT) is an emerging imaging technique that reconstructs conductivity images using magnetic flux density measurements acquired employing MRI together with conventional EIT measurements. In this study, experimental MR-EIT images from phantoms with conducting and insulator objects are presented. The technique is implemented using the 0.15 T Middle East Technical University MRI system. The dc current method used in magnetic resonance current density imaging is adopted. A reconstruction algorithm based on the sensitivity matrix relation between conductivity and only one component of magnetic flux distribution is used. Therefore, the requirement for object rotation is eliminated. Once the relative conductivity distribution is found, it is scaled using the peripheral voltage measurements to obtain the absolute conductivity distribution. Images of several insulator and conductor objects in saline filled phantoms are reconstructed. The L2 norm of relative error in conductivity values is found to be 13%, 17% and 14% for three different conductivity distributions.

Current constrained voltage scaled reconstruction (CCVSR) algorithm for MR-EIT and its performance with different probing current patterns.

Conventional injected-current electrical impedance tomography (EIT) and magnetic resonance imaging (MRI) techniques can be combined to reconstruct high resolution true conductivity images. The magnetic flux density distribution generated by the internal current density distribution is extracted from MR phase images. This information is used to form a fine detailed conductivity image using an Ohm's law based update equation. The reconstructed conductivity image is assumed to differ from the true image by a scale factor. EIT surface potential measurements are then used to scale the reconstructed image in order to find the true conductivity values. This process is iterated until a stopping criterion is met. Several simulations are carried out for opposite and cosine current injection patterns to select the best current injection pattern for a 2D thorax model. The contrast resolution and accuracy of the proposed algorithm are also studied. In all simulation studies, realistic noise models for voltage and magnetic flux density measurements are used. It is shown that, in contrast to the conventional EIT techniques, the proposed method has the capability of reconstructing conductivity images with uniform and high spatial resolution. The spatial resolution is limited by the larger element size of the finite element mesh and twice the magnetic resonance image pixel size.