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Ionizing radiation is classified as a potent carcinogen, and its injury to living cells to a large extent due to oxidative stress. Direct and indirect interaction of ionizing radiation responsible to cell injury. The direct action produces disruption of sensitive molecules in the cells. Where as the indirect effects results from its interaction with water molecules. Which result in the production of highly reactive free radicals such as OH, H and e and their subsequent action on subcellular structures.

Melatonin the chief secretory product of pineal gland in the brain is a ubiquitously acting molecule with several functions in hundred of investigations, melatonin has been documented as a direct free radical scavenger and an indirect antioxidant the hydroxyl radical scavenging ability of melatonin was used as a rationale to determine its radio protective efficiency indeed the result from many in vitro and in vivo investigation have confirmed that melatonin protects mammalian cells from the toxic effects of ionizing radiation. The radioprotective effects of melatonin against cellular damage caused by oxidative stress and its low toxicity make this molecule a potential supplement in the treatment or co-treatment in situations where the effects of ionizing radiation are to be minimized.

The multipurpose beam delivery system of the experimental complex of INR RAS is being designed for organization of the simultaneous operation of neutron experimental installations and proton treatment facility driven by the MMF proton linac. This system increases considerably the effectiveness of linac operation. The system may support the high beam current for neutron experiments and quite low (5–6 orders of magnitude lower) for proton treatment facility. The fast magnetic deflector and moveable electrostatic deflector are included into the system. The expected characteristics of the system are described.

The construction of a new radiological centre, based on INR proton linac in Troitsk near Moscow, is now in progress. Its 1-st stage with one horizontal-beam treatment room and one conventional-therapy treatment room will be completed and put in action during one year. The proton linac energy variation (70 – 250 MeV) and the patient chair design will allow to treat any tumors from eye tumors up to 10 cm wide deep-sited tumors. The boost method, combining conventional radiotherapy and proton therapy, will increase the effectiveness of linac work. Very thin multichannel ion chambers, the patient chair, a new individual beam formation system, a digital x-ray position control system and others original systems were developed in INR for the purposes of the centre. On the first stage, the dose will be delivered by the passive scattering method. However, the linac beam parameters are suitable for the beam scanning as well. The next stage of the centre may include a non-horizontal beam treatment room (gantry or vertical beam) and the beam scanning. The proton accelerator and the beam channel were designed for the simultaneous acceleration and delivering of several beams. This allows to combine the patient treatment with the isotope production and scientific work, for example, on neutron sources. One of possible applications of the parallel beams is the neutron capture radiotherapy with the help of gadolinium or other targeting materials since the neutron flux may be sufficiently high. Taking into account that several radioisotopes, including short living ones, may be produced and applied in the same place, the INR centre may become a really universal radiological centre for the practical radiotherapy and researches in this field.

An analytical integration of Bethe-Bloch equation is presented to provide the energy E(z) as a function of z and dE/dz. Together with multiple scatter the influence of collimators to depth dose curves and a profile is studied and compared with GEANT4.

Since June 2002 we have treated 28 patients with prostate cancer and 2 patients with liver cancer using the accelerator complex that consists of a 5 MV tandem and a 200 MeV synchrotron (W-MAST). The QA/QC activities for proton therapy at WERC has been performed such as the check of the soundness of the irradiation system including the monitors system, ridge filters, compensators, wobbler magnets, and water and air systems, and the positioning system including positioning with CT installed adjacent to the irradiation port and so on. We report the details of the QA/QC activities that are performed daily, weekly and yearly, and results like the long-term trend of the dose monitor in WERC. In addition we show some experiences that prevent therapeutic troubles from occurring due to the systematic and human errors.

In order to check the presence of spinal deformity in the early stage, orthopedists have traditionally performed on children a painless examination called a forward- bending test in school screening. In forward-bending test, mainly medical doctor checks to see if one shoulder is lower than the other. But this test is neither reproductive nor objective. Moreover, the inspection takes much time when applied to medical examination in schools. To overcome these difficulties, a moire method has been proposed which takes moire topographic images of human subject backs and checks symmetry/asymmetry of the moire patterns in a twodimensional way on visual screening. In this paper, we propose a new technique for automatic detection of spinal deformity from moire topographic images. In the first stage, once the original moire image is fed into computer, the middle line of the subject’s back is extracted on the moire image by employing the approximate symmetry analysis. Regions of interest are then automatically selected on the moire image from its upper part to the lower part. Numerical representation of the degree of asymmetry is therefore useful in evaluating the deformity. Displacement of local centroids and difference of gray value are calculated between the left-hand side and the right-hand side regions of the moire images with respect to the extracted middle line. Extracted 4 feature vectors (mean value and standard deviation from the each displacement) from the left-hand side and right-hand side rectangle areas are applied to train the Neural Network (NN), Support Vector Machines (SVMs). In the final stage, normal and abnormal cases are classified by NN and SVM. An experiment was performed employing 1,200 real moire images based on NN and SVMs, and classification rates of 90.3% and 85.3% was achieved respectively.

Region growing is an old and well-known technique, which in this work is applied to the tracing of bronchial and vascular trees in thin slice CT scans of the lungs. Classical problems of region growing are selection of seedpoint, sensitivity to seedpoint selection, stopping criterion, and long processing times in the case of large images. An alternative implementation was developed as combined thresholding and connected component labeling approach. Speedup is drastic. This new approach is particularly well adapted to CT images, where the intensities have a physical significance, hence thresholds are more significant than seed intensity and stopping criterion. As an added advantage, sensitivity to seed selection and stopping criterion is significantly reduced. Automated processing is implemented for seed selection — by incorporating the results of simple segmentation-and-labeling systems — and the optimal threshold — by analyzing the break-point in the volume of the resulting segment in function of the threshold. The main problem faced in the segmentation of the bronchial tree is the “leaking” of the segment in the background: the segment is composed of air (low intensity), surrounded by soft tissue (high intensity) which separates it from the surrounding lung tissue (any intensity between air and soft tissue due to partial volume effects). Once the intensity of the bronchial envelope drops due to partial volume effects, the region growing algorithm “leaks” through the “dip” and “inundates” the pulmonary cavity instead of following the main bronchus. This causes a sudden drastic increase in the volume of the segment which can be detected and used to limit the threshold value so as to avoid this “leaking”. One “leak” could affect the segmentation of the whole bronchial tree, hence we decided to isolate individual “leaks” by applying a Quadtree approach, helping to detect more of the distal bronchial tree.

A computer-aided diagnosis (CAD) system has been examined to reduce the effort of radiologist. In the mammogram, it is helpful to improve the diagnostic accuracy of malignancy microcalcifications in early stage of detecting breast cancer. In this paper, we propose a microcalcification detection method using multi-layer support vector machine (SVM) classifiers to determine whether microcalcifications are malignant or benign tumors. The proposed microcalcification detection is divided into two steps, each of which uses a SVM classifier. First, potential ROIs (Region of interest) those are suspicious as malignant tumors are detected as a coarse detection level. And then, each ROI is classified whether it is malignant or not. The proposed algorithm is applied to the Korean digital mammogram. Experimental result showed that the proposed method would outperform conventional method using ANN (artificial neural networks).

Three-dimensional wavelet transform (3D-WT) has been proposed as basis for volumetric data coding, because it can provide lossless coding and top-quality reconstruction. These functionalities are very important for medical imaging. There are two different ways to perform the WT: the Non Standard or Classic WT versus the Standard WT. The latter is practically rejected for state-of-the-art coders because it demands more computing time. However, if it is lightly changed, it can deliver wavelet coefficients that get more coding efficiency with a little cost in time terms. In this paper we propose three 3D Standard WT-based decomposition algorithms that are able to prepare the wavelet coefficients during the spatial and temporal decomposition processes to reduce the most redundancy in data. We have conducted a set of experimental evaluations for a representative data set of a modality of intrinsically volumetric medical imaging: angiography sequences.

In this study the evaluation of a Platelet-based Maximum Penalized Likelihood Estimation (MPLE) for denoising SPECT images was performed and compared with other denoising methods such as Wavelets or Butterworth filteration. Platelet-based MPLE factorization as a multiscale decomposition approach has been already proposed for better edges and surfaces representation due to Poisson noise and inherent smoothness of this kind of images.

We applied this approach on both simulated and real SPECT images. For NEMA phantom images, the measured noise levels before (M) and after (M) denoising with Plateletbased MPLE approach were M=2.1732, M=0.1399. In patient study for 32 cardiac SPECT images, the difference between noise level and SNR before and after the approach were (M=3.7607, SNR=9.7762, M=0.7374, SNR=41.0848) respectively. Thus the Coefficient Variance (C.V) of SNR values for denoised images with this algorithm as compared with Butterworth filter, (145/33%) was found. For 32 brain SPECT images the Coefficient Variance of SNR values, (196/17%) was obtained.

Our results shows that Platelet-based MPLE is a useful method for denoising SPECT images considering better homogenous image, improvements in SNR, better radioactive uptake in target organ and reduction of interfering activity from background radiation in compare with that of other conventional denoising methods.