Multiparametric prostate MRI quality assessment using a semi-automated PI-QUAL software program

The technical requirements for the acquisition of multiparametric magnetic resonance imaging (mpMRI) of the prostate have been clearly outlined in the Prostate Imaging Reporting and Data System (PI-RADS) guidelines, but there is still huge variability in image quality among centres across the world. It has been difficult to quantify what constitutes a good-quality image, and a first attempt to address this matter has been the publication of the Prostate Imaging Quality (PI-QUAL) score and its dedicated scoring sheet. This score includes the assessment of technical parameters that can be obtained from the DICOM files along with a visual evaluation of certain features on prostate MRI (e.g., anatomical structures). We retrospectively analysed the image quality of 10 scans from different vendors and magnets using a semiautomated dedicated PI-QUAL software program and compared the time needed for assessing image quality using two methods (semiautomated assessment versus manual filling of the scoring sheet). This semiautomated software is able to assess the technical parameters automatically, but the visual assessment is still performed by the radiologist. There was a significant reduction in the reporting time of prostate mpMRI quality according to PI-QUAL using the dedicated software program compared to manual filling (5′54″ versus 7′59″; p = 0.005). A semiautomated PI-QUAL software program allows the radiologist to assess the technical details related to the image quality of prostate mpMRI in a quick and reliable manner, allowing clinicians to have more confidence that the quality of mpMRI of the prostate is sufficient to determine patient care.

Efek Perubahan Dosis Radiasi Dan Kualitas Gambar Pada Hasil Radiograph Dengan Luas Kolimasi Berbeda

Background: The use of variations of collimation will provide a low dose to the patient and radiographic results that provide a good quality image. This research is to examine the effects of various collimation sizes on the image quality and radiation doses when using x-ray machine at Radiology laboratory of Al-Islam Polytechnic, Bandung. How much the change in density values that occur and to find out of scattering radiation received by the patient in the Radiology laboratory of Al-Islam Polytechnic, Bandung.Methods: This type of research is an experimental study with participatory observation data collection. at the Radiology Laboratory of the Al-Islam Polytechnic, Bandung The independent variable is variations of collimation, the dependent variables are quality image and doses radiation. Data collection was carried out by exposing a Stepwedge stored on a 35 x 35 cm radiographic cassette with different irradiation areas and pendose as a measure of radiation. Radiograph results were analyzed by a densitometer. Then the results will be analyzed using digraph to know the movement of each different irradiation field area.Results: The results showed that there were influences of changes in the variation of collimation. Density value and scattered radiation of each different irradiation field area produces are different values. The smaller area of the irradiation field. Is, the higher density value and low dose. Thus, to get the best density value and the low dose is required to reduce the width of the collimation field conducted.Conclusions: There was an influence variation of collimation on the quality of the image and dose to the patient.

FIRST ASSESSMENTS ON HERITAGE SCIENCE ORIENTED IMAGE-BASED MODELING USING LOW-COST MODIFIED AND MOBILE CAMERAS

Three-dimensional modeling of cultural heritage, especially concerning large scale studies, as for example, archaeometry, diagnostics and conservation intervention applications, which usually require high-resolution and multi-spectral analyses, necessitates the use of complicate and often expensive equipment. Recent developments regarding low-cost commercially available spectrally modified digital reflex cameras, smartphones with good quality image sensors, mobile thermal cameras in combination with automated or semi-automated photogrammetric software implementing Structure from Motion (SfM) and Multiview Stereo (MVS) algorithms constitute some cheaper and simpler alternatives. Although, the results of the integration of these types of sensors and techniques are often not evaluated as metric products. The presented research combines the above-mentioned instrumentation and software to implement and evaluate low-cost 3D modeling solutions on heritage science-oriented case studies, but also to perform some first assessments on the resulting models' metric properties, quality of texture and usefulness for further scientific investigations.

Comparative analysis between non-linear wavelet based image denoising techniques

Digital images have been a major form of transmission of visual information, but due to the presence of noise, the image gets corrupted. Thus, processing of the received image needs to be done before being used in an application. Denoising of image involves data manipulation to remove noise in order to produce a good quality image retaining different details. Quantitative measures have been used to show the improvement in the quality of the restored image by the use of various thresholding techniques by the use of parameters mainly, MSE (Mean Square Error), PSNR (Peak-Signal-to-Noise-Ratio) and SSIM (Structural Similarity index). Here, non-linear wavelet transform denoising techniques of natural images are studied, analyzed and compared using thresholding techniques such as soft, hard, semi-soft, LevelShrink, SUREShrink, VisuShrink and BayesShrink. On most of the tests, PSNR and SSIM values for LevelShrink Hard thresholding method is higher as compared to other thresholding methods. For instance, from tests PSNR and SSIM values of lena image for VISUShrink Hard, VISUShrink Soft, VISUShrink Semi Soft, LevelShrink Hard, LevelShrink Soft, LevelShrink Semi Soft, SUREShrink, BayesShrink thresholding methods at the variance of 10 are 23.82, 16.51, 23.25, 24.48, 23.25, 20.67, 23.42, 23.14 and 0.28, 0.28, 0.28, 0.29, 0.22, 0.25, 0.16 respectively which shows that the PSNR and SSIM values for LevelShrink Hard thresholding method is higher as compared to other thresholding methods, and so on. Thus, it can be stated that the performance of LevelShrink Hard thresholding method is better on most of tests.

OBJECT QUALITY ENHANCEMENT OF MULTI-FRAME LOW-RESOLUTION VIDEO

A good quality image is required in various applications such as object identification and authentication. This research presents the performance of image resolution enhancement method, in which the low-resolution image originated from low-resolution CCTV video. The enhancement method is initialized by averaging video frames and continued by interpolating the resulted images using the existing interpolation techniques, namely bilinear, bi-cubic, nearest neighbor and spleen. Frame rate of 15 and 25 frames per second (fps) has been applied to the testing video. The result shows that the differences of frame rate and number of the averaged frame would affect image quality. Subjective assessment of respondents of MOS above 3 has been obtained by increasing the frame rate and the number of averaging frames.

More accurate neuronavigation data provided by biomechanical modeling instead of rigid registration

It is possible to improve neuronavigation during image-guided surgery by warping the high-quality preoperative brain images so that they correspond with the current intraoperative configuration of the brain. In this paper, the accuracy of registration results obtained using comprehensive biomechanical models is compared with the accuracy of rigid registration, the technology currently available to patients. This comparison allows investigation into whether biomechanical modeling provides good-quality image data for neuronavigation for a larger proportion of patients than rigid registration. Preoperative images for 33 neurosurgery cases were warped onto their respective intraoperative configurations using both the biomechanics-based method and rigid registration. The Hausdorff distance–based evaluation process, which measures the difference between images, was used to quantify the performance of both registration methods. A statistical test for difference in proportions was conducted to evaluate the null hypothesis that the proportion of patients for whom improved neuronavigation can be achieved is the same for rigid and biomechanics-based registration. The null hypothesis was confidently rejected (p < 10−4). Even the modified hypothesis that fewer than 25% of patients would benefit from the use of biomechanics-based registration was rejected at a significance level of 5% (p = 0.02). The biomechanics-based method proved particularly effective in cases demonstrating large craniotomy-induced brain deformations. The outcome of this analysis suggests that nonlinear biomechanics-based methods are beneficial to a large proportion of patients and can be considered for use in the operating theater as a possible means of improving neuronavigation and surgical outcomes.

A SPATIAL DOMAIN OBJECT SEPARABILITY BASED NO-REFERENCE IMAGE QUALITY MEASURE USING MEAN AND VARIANCE

In many modern image processing applications determining quality of the image is one of the most challenging tasks. Researchers working in the field of image quality assessment design algorithms for measuring and quantifying image quality. The human eye can identify the difference between a good quality image and a noisy image by simply looking at the image, but designing a computer algorithm to automatically determine the quality of an image is a very challenging task. In this paper, we propose an image quality measure using the concept of object separability. We define object separability using variance. Two objects are very well separated if variance of individual object is less and mean pixel values of neighboring objects are very different. Degradation in images can be due to a number of reasons like additive noises, quantization defects, sampling defects, etc. The proposed no-reference image quality measure will determine quality of degraded images and differentiate between good and degraded images.

Study on Coarse Aggregate Gradation Analysis of Cement Treated Base Course Based on Core Sample Image

In order to get the coarse aggregate particle gradation of cement treated base course core sample dilled form the pavement, an image acquisition system is designed. The system mainly contains an Aviiva ® M2 CL line scan camera, a core sample rotation platform and a LED light source. The software are designed and implemented by using the Matrox Mil controls in the Visual Studio VB.NET. Test results show that when the camera exposure time is set to 800μs, good quality image of core sample can be obtained. In the study, the original core sample images of cement treated aggregate were improved by rescaling of each pixel, then were binarized by using adaptive threshold method. After getting the binary image, morphological operations were carried out to deal with the conglutinations of the particles. Next, characteristics of each particle, such as area, perimeter, fitting ellipse and minFeret were extracted to calculate the area passing rate of aggregate with different size. Results shows that, in this way, the gradation of coarse aggregate (>2.36mm) can be got and the method helps to get the coarse aggregate particle distribution of cement treated aggregate core sample quickly.

FLEXIBLE IMAGE BLENDING FOR IMAGE MOSAICING WITH REDUCED ARTIFACTS

Image mosaicing involves geometric alignment among video frames and image compositing or blending. For dynamic mosaicing, image mosaics are constructed dynamically along with incoming video frames. Consequently, dynamic mosaicing demands efficient operations for both alignment and blending in order to achieve real-time performance. In this paper, we focus on efficient image blending methods that create good-quality image mosaics from any number of overlapping frames. One of the driving forces for efficient image processing is the huge market of mobile devices such as cell phones, PDAs that have image sensors and processors. In particular, we show that it is possible to have efficient sequential implementations of blending methods that simultaneously involve all accumulated video frames. The choices of image blending include traditional averaging, overlapping and flexible ones that take into consideration temporal order of video frames and user control inputs. In addition, we show that artifacts due to mis-alignment, image intensity difference can be significantly reduced by efficiently applying weighting functions when blending video frames. These weighting functions are based on pixel locations in a frame, view perspective and temporal order of this frame. One interesting application of flexible blending is to visualize moving objects on a mosaiced stationary background. Finally, to correct for significant exposure difference in video frames, we propose a pyramid extension based on intensity matching of aligned images at the coarsest resolution. Our experiments with real image sequences demonstrate the advantages of the proposed methods.