Medical X-ray Imaging Research Articles

A new approach for image stitching technique using Dynamic Time Warping (DTW) algorithm towards scoliosis X-ray diagnosis

Consider a set of images of a single object, or scenery, taken from different viewpoints and time. Panorama image creation is the process of stitching such images into a single coordinate system to generate a wider viewing panoramic image. Image stitching consists of two processes which are image registration and image blending. In image registration, parts of two overlapping or consecutive images are considered to find an appropriate merging position and transformation to combine the images. In image blending, the intensities of pixels along the stitching line are modified so that they flow naturally without any noticeable break. In this paper, we propose a novel method that utilizes the Dynamic Time Warping (DTW) algorithm to match pairs of images for image stitching. We also perform a dimension reduction scheme that significantly reduces the computational complexity of the standard DTW without affecting its performance. The effectiveness of the proposed method is demonstrated in stitching 50 pairs of medical X-ray images and its performance is compared to those of normalized cross correlation (NCC), Minimum Average Correlation Energy (MACE) filters, sum-of-square-differences (SSD) and sum-of-absolute-differences (SAD). For the database used, the dimensionally reduced DTW outperforms the NCC, MACE, SSD and SAD methods in accuracy and average execution time. The method also outperforms two widely used stitching programs available on the internet called Hugin and Autostitch.

A model for comparative analysis of medical bone X-ray images using image segmentation

Image enhancement is the pre-processing stage of the image processing. The objective is to improve the visual effects and the perception of knowledge in images for viewers and to provide a better input for automated image processing technique. It gives emphasis on the whole or part features of the graphics in the designated image applications to enlarge the objects in the graphics. The enhanced image by use of threshold segmentation method identifies bone fracture in medical X-ray images. In this research work, the image is taken as input and after noise removal, the X-ray image of right hand and hairline bone fracture image is being segmented using simple thresholding, multiple thresholding and optimal thresholding method and compared with each other so as to choose the best technique for threshold image segmentation.

Novel Technique for Performance Improvement of the Wavelet based Denoising Algorithms using Rotated Wavelet Filters

Donoho is the first who put forward wavelet transform based image denoising in year 1994 and the craze of wavelet based image denoising algorithm is observed till today. Now a days some researchers move ahead with advanced wavelet transforms like Curvelet, Contourlet etc. for image denoising algorithms due to superiority of these transforms w.r.t. directional selectivity, ability to give sparse representations for curves, singularities and geometric features in an image compared to wavelet transform. But popularity of some wavelet based algorithms is still observed. In this paper, author proposed technique using Rotated wavelet filter (RWF) to improve the performance of wavelet based denoising algorithms. The proposed methodology tested for general and medical (Ultrasound and X-Ray) images and proved significant improvements in quality measures PSNR and SSIM compared with the regular wavelet based approaches. The advantage of this proposed work is computational complexity which is same as discrete wavelet transform based algorithms in 2-D frequency domain platform and less execution time compare to BM3D algorithm.

Characterization of MOSFET Dosimeter Angular Response Using a Spherical Phantom for Fluoroscopic Dosimetry.

Metal-Oxide Semiconductor Field-Effect Transistor (MOSFET) dosimeters, placed in anthropomorphic phantoms, are a standard method for organ dosimetry in medical x-ray imaging applications. However, many x-ray applications, particularly fluoroscopy procedures, use variable projection angles. During dosimetry, the MOSFET detector active area may not always be perpendicular to the x-ray beam. The goal of this study was to characterize the dosimeter's angular response in the fluoroscopic irradiation involved in pediatric cardiac catheterization procedures, during which a considerable amount of fluoroscopic x-ray irradiation is often applied from various projection angles. A biological x-ray irradiator was used to simulate the beam quality of a biplane fluoroscopy imaging system. A custom-designed acrylic spherical scatter phantom was fabricated to measure dosimeter response (in mV) in two rotational axes, axial (ψ) and normal-to-axial (θ), in 30° increments, as well as four common oblique angles used in cardiac catheterization: a) 90° Left Anterior Oblique (LAO); b) 70° LAO/ 20° Cranial; c) 20° LAO/ 15° Cranial; and d) 30° Right Anterior Oblique (RAO). All results were normalized to the angle where the dosimeter epoxy is perpendicular to the beam or the Posterior-Anterior projection angle in the clinical setup. The relative response in the axial rotation was isotropic (within ± 10% deviation); that in the normal-to-axial rotation was isotropic in all angles except the ψ = 270° angle, where the relative response was 83 ± 9%. No significant deviation in detector response was observed in the four common oblique angles, with their relative responses being: a) 102 ± 3%; b) 90 ± 3%; c) 92 ± 3%; and d) 95 ± 3%, respectively. These angular correction factors will be used in future dosimetry studies for fluoroscopy. The spherical phantom may be useful for other applications, as it allows the measurement of dosimeter response in virtually all angles in the 3-dimensional spherical coordinates.

Anthropomorphic model observer performance in three-dimensional detection task for low-contrast computed tomography.

X-ray medical imaging is increasingly becoming three-dimensional (3-D). The dose to the population and its management are of special concern in computed tomography (CT). Task-based methods with model observers to assess the dose-image quality trade-off are promising tools, but they still need to be validated for real volumetric images. The purpose of the present work is to evaluate anthropomorphic model observers in 3-D detection tasks for low-contrast CT images. We scanned a low-contrast phantom containing four types of signals at three dose levels and used two reconstruction algorithms. We implemented a multislice model observer based on the channelized Hotelling observer (msCHO) with anthropomorphic channels and investigated different internal noise methods. We found a good correlation for all tested model observers. These results suggest that the msCHO can be used as a relevant task-based method to evaluate low-contrast detection for CT and optimize scan protocols to lower dose in an efficient way.

Volumetric CT with sparse detector arrays (and application to Si-strip photon counters)

Novel x-ray medical imaging sensors, such as photon counting detectors (PCDs) and large area CCD and CMOS cameras can involve irregular and/or sparse sampling of the detector plane. Application of such detectors to CT involves undersampling that is markedly different from the commonly considered case of sparse angular sampling. This work investigates volumetric sampling in CT systems incorporating sparsely sampled detectors with axial and helical scan orbits and evaluates performance of model-based image reconstruction (MBIR) with spatially varying regularization in mitigating artifacts due to sparse detector sampling.Volumetric metrics of sampling density and uniformity were introduced. Penalized-likelihood MBIR with a spatially varying penalty that homogenized resolution by accounting for variations in local sampling density (i.e. detector gaps) was evaluated. The proposed methodology was tested in simulations and on an imaging bench based on a Si-strip PCD (total area 5 cm × 25 cm) consisting of an arrangement of line sensors separated by gaps of up to 2.5 mm. The bench was equipped with translation/rotation stages allowing a variety of scanning trajectories, ranging from a simple axial acquisition to helical scans with variable pitch. Statistical (spherical clutter) and anthropomorphic (hand) phantoms were considered. Image quality was compared to that obtained with a conventional uniform penalty in terms of structural similarity index (SSIM), image uniformity, spatial resolution, contrast, and noise.Scan trajectories with intermediate helical width (~10 mm longitudinal distance per 360° rotation) demonstrated optimal tradeoff between the average sampling density and the homogeneity of sampling throughout the volume. For a scan trajectory with 10.8 mm helical width, the spatially varying penalty resulted in significant visual reduction of sampling artifacts, confirmed by a 10% reduction in minimum SSIM (from 0.88 to 0.8) and a 40% reduction in the dispersion of SSIM in the volume compared to the constant penalty (both penalties applied at optimal regularization strength). Images of the spherical clutter and wrist phantoms confirmed the advantages of the spatially varying penalty, showing a 25% improvement in image uniformity and 1.8 × higher CNR (at matched spatial resolution) compared to the constant penalty.The studies elucidate the relationship between sampling in the detector plane, acquisition orbit, sampling of the reconstructed volume, and the resulting image quality. They also demonstrate the benefit of spatially varying regularization in MBIR for scenarios with irregular sampling patterns. Such findings are important and integral to the incorporation of a sparsely sampled Si-strip PCD in CT imaging.

VIEW CLASSIFICATION OF MEDICAL X-RAY IMAGES USING PNN CLASSIFIER, DECISION TREE ALGORITHM AND SVM CLASSIFIER

In this era of electronic advancements in the field of medical image processing, the quantum of medical X-ray images so produced exorbitantly can be effectively addressed by means of automated indexing, comparing, analysing and annotating that will really be pivotal to the radiologists in interpreting and diagnosing the diseases. In order to envisage such an objective, it has been humbly endeavoured in this paper by proposing an efficient methodology that takes care of the view classification of the X-ray images for the automated annotation from their vast database, with which the decision making for the physicians and radiologists becomes simpler despite an immeasurable and ever-growing trends of the X-ray images. In this paper, X-ray images of six different classes namely chest, head, foot, palm, spine and neck have been collected. The framework proposed in this paper involves the following: The images are pre-processed using M3 filter and segmentation by Expectation Maximization (EM) algorithm, followed by feature extraction through Discrete Wavelet Transform. The orientation of X-ray images has been performed in this work by comparing among the Probabilistic Neural Network (PNN), Decision Tree algorithm and Support Vector Machine (SVM), while the PNN yields an accuracy of 75%, the Decision Tree with 92.77% and the SVM of 93.33%.

Matching methods evaluation framework for stereoscopic breast x-ray images.

Three-dimensional (3-D) imaging has been intensively studied in the past few decades. Depth information is an important added value of 3-D systems over two-dimensional systems. Special focuses were devoted to the development of stereo matching methods for the generation of disparity maps (i.e., depth information within a 3-D scene). Dedicated frameworks were designed to evaluate and rank the performance of different stereo matching methods but never considering x-ray medical images. Yet, 3-D x-ray acquisition systems and 3-D medical displays have already been introduced into the diagnostic market. To access the depth information within x-ray stereoscopic images, computing accurate disparity maps is essential. We aimed at developing a framework dedicated to x-ray stereoscopic breast images used to evaluate and rank several stereo matching methods. A multiresolution pyramid optimization approach was integrated to the framework to increase the accuracy and the efficiency of the stereo matching techniques. Finally, a metric was designed to score the results of the stereo matching compared with the ground truth. Eight methods were evaluated and four of them [locally scaled sum of absolute differences (LSAD), zero mean sum of absolute differences, zero mean sum of squared differences, and locally scaled mean sum of squared differences] appeared to perform equally good with an average error score of 0.04 (0 is the perfect matching). LSAD was selected for generating the disparity maps.

Current studies and future perspectives of synchrotron radiation imaging trials in human patients

The coherent and monochromatic x-ray beams available at the synchrotron radiation (SR) laboratories are ideal tools for the development and the initial application of new imaging techniques. In the present paper the history of the clinical studies in k-edge subtraction imaging with SR is summarized, including coronary angiography and bronchography. The results of the recent trial in phase-contrast mammography at Elettra (Trieste, Italy) are discussed, in order to assess the clinical impact of the new imaging modality and the potential interest in its translation to clinical practice. The direct measurement of linear attenuation coefficient obtained during the SR mammography trial is also discussed.The new program of phase-contrast breast CT under development at Elettra is presented. Recently, 3D breast imaging (tomosynthesis and cone beam breast CT) has been introduced in clinical practice with significant improvement in diagnostic accuracy. The aim of this research is to study the contribution of the phase-contrast to the image quality of breast CT.Increasing the image quality of the x-ray medical images at the level of the results obtained at the SR laboratories is highly desirable, hence the promising techniques for the translation of the phase-contrast imaging to the hospitals are briefly discussed.

X-ray imaging with scintillator-sensitized hybrid organic photodetectors

Medical X-ray imaging requires cost-effective and high-resolution flat-panel detectors for the energy range between 20 and 120 keV. Solution-processed photodetectors provide the opportunity to fabricate detectors with a large active area at low cost. Here, we present a disruptive approach that improves the resolution of such detectors by incorporating terbium-doped gadolinium oxysulfide scintillator particles into an organic photodetector matrix. The X-ray induced light emission from the scintillators is absorbed within hundreds of nanometres, which is negligible compared with the pixel size. Hence, optical crosstalk, a limiting factor in the resolution of scintillator-based X-ray detectors, is minimized. The concept is validated with a 256 × 256 pixel detector with a resolution of 4.75 lp mm−1 at a MTF = 0.2, significantly better than previous stacked scintillator-based flat-panel detectors. We achieved a resolution that proves the feasibility of solution-based detectors in medical applications. Time-resolved electrical characterization showed enhanced charge carrier mobility with increased scintillator filling, which is explained by morphological changes.

Update on radiation safety and dose reduction in pediatric neuroradiology.

The number of medical X-ray imaging procedures is growing exponentially across the globe. Even though the overall benefit from medical X-ray imaging procedures far outweighs any associated risks, it is crucial to take all necessary steps to minimize radiation risks to children without jeopardizing image quality. Among the X-ray imaging studies, except for interventional fluoroscopy procedures, CT studies constitute higher dose and therefore draw considerable scrutiny. A number of technological advances have provided ways for better and safer CT imaging. This article provides an update on the radiation safety of patients and staff and discusses dose optimization in medical X-ray imaging within pediatric neuroradiology.

Grating-based interferometry and hybrid photon counting detectors: Towards a new era in X-ray medical imaging

Progress in X-ray medical imaging and advances in detector developments have always been closely related. Similarly, a strong connection exists between innovations in synchrotron imaging and their implementation on table-top X-ray tube setups. The transfer of phase-based imaging to X-ray tubes can provide table-top setups with improved contrast between areas of low attenuation differences, by exploiting the unit decrement of the real part of the refractive index. Medical imaging is a potential application for such a system. Originally developed for synchrotron experiments, the novel generation of hybrid photon counting detectors is becoming increasingly popular due to their unique characteristics, such as small pixel size, negligible dark noise, fast counting and adjustable energy thresholds. Furthermore, novel room temperature semiconductor materials such as Cd(Zn)Te can provide higher quantum efficiency. In the first part of this article we review phase-contrast techniques and recent research towards medical applications. In the second part we present results and evaluate the potential of combining a table-top Talbot grating interferometry system with latest generation hybrid photon counting detectors.

Realistic wave-optics simulation of X-ray phase-contrast imaging at a human scale.

X-ray phase-contrast imaging (XPCI) can dramatically improve soft tissue contrast in X-ray medical imaging. Despite worldwide efforts to develop novel XPCI systems, a numerical framework to rigorously predict the performance of a clinical XPCI system at a human scale is not yet available. We have developed such a tool by combining a numerical anthropomorphic phantom defined with non-uniform rational B-splines (NURBS) and a wave optics-based simulator that can accurately capture the phase-contrast signal from a human-scaled numerical phantom. Using a synchrotron-based, high-performance XPCI system, we provide qualitative comparison between simulated and experimental images. Our tool can be used to simulate the performance of XPCI on various disease entities and compare proposed XPCI systems in an unbiased manner.

An Optimal Method to Improve the Visual Quality of Medical Images

AbstractAs the visual quality of X-ray images is a critical reference for the accuracy of the clinical diagnosis, the methods toimprove the quality of X-ray images have been investigated. Among many existing methods, using frequency domainfilter is a very powerful method to improve the visual quality of images. In this paper, the inherent noises of the inputimages are suppressed by adding the Laplacian image to the subjected image. The medical X-ray images using the optimalhigh pass filter has shown improved edges. Further, the optimal high frequency emphasis filter has shown the improvedcontrast of flat areas by using the result image from the optimal high pass filter. Also the resulting images of the globalcontrast have improved by the histogram equalization. As a result, the proposed methods have shown enhanced contrastand edges of the images with noise canceling effect. Keywords: Laplacian Image, High Pass Filter, High Frequency Emphasis Filter 1. Introduction Even the smallest abnormality should not be over-looked in the correct X-ray diagnosis because the earlytreatment of this abnormality is critical for the recoveryof patients. To identify abnormalities in lung tissue thatare roughly spherical with round opacity and a diameterof up to approximately 30 mm

A New Hybrid Approach Toward Spinal Deformities’ Radiographic Images Diagnosis

In this study, a new hybrid method of Image stitching that utilizes both advantages of feature based and direct based methods to identify and merge pairs of x-ray medical images is presented. The performance of the proposed method based on this hybrid approach is investigated and discussed. The ability of the method to classify overlapping pairs of images is demonstrated. It is observed that the proposed method displays comparable or superior performance to the SIFT method described in the literature on the standard databases. These results reveal the potential of the proposed method for further development to tackle more advanced stitching problems.

A posteriori correction of camera characteristics from large image data sets.

Large datasets are emerging in many fields of image processing including: electron microscopy, light microscopy, medical X-ray imaging, astronomy, etc. Novel computer-controlled instrumentation facilitates the collection of very large datasets containing thousands of individual digital images. In single-particle cryogenic electron microscopy (“cryo-EM”), for example, large datasets are required for achieving quasi-atomic resolution structures of biological complexes. Based on the collected data alone, large datasets allow us to precisely determine the statistical properties of the imaging sensor on a pixel-by-pixel basis, independent of any “a priori” normalization routinely applied to the raw image data during collection (“flat field correction”). Our straightforward “a posteriori” correction yields clean linear images as can be verified by Fourier Ring Correlation (FRC), illustrating the statistical independence of the corrected images over all spatial frequencies. The image sensor characteristics can also be measured continuously and used for correcting upcoming images.

Towards thin-film self-powered radiation detectors employing disparate conductive layers

A new class of self-powered thin film radiation detectors is experimentally explored via their IV-curve characteristics. These detectors are parallel-plane microstructures composed of disparate atomic number (Z) thin-film electrodes separated by air gaps. Large radiation-induced electron currents (RIC) are observed for zero external voltage bias. Compared to ionization chambers (composed of macroscopic non-disparate low-Z electrodes), this anomalous behavior is due to two independent effects: traversal of fast electrons leaking from the high-Z cathodes and the auto-collection of ionization electrons from the air gap due to the presence of contact potential. The zero voltage current reaches up to 80% of the saturation current measured for non-zero bias voltages. The magnitude of saturation currents increases with the total anode and cathode atomic numbers. The stopping potentials (i.e., external voltage bias resulting in zero RIC current) correspond to the differences in the electrodes’ work functions (the contact potential) modified by the contributions from the fast electron current formed by the leaking electrons. These features make the thin film detector attractive for applications in x-ray medical or industrial imaging, dosimetry and radiation protection.

Readout cross-talk for alpha-particle measurements in a pixelated sensor system

Simulations in Medici are performed to quantify crosstalk and charge sharing in a hybrid pixelated silicon detector. Crosstalk and charge sharing degrades the spatial and spectral resolution of single photon processing X-ray imaging systems. For typical medical X-ray imaging applications, the process is dominated by charge sharing between the pixels in the sensor. For heavier particles each impact generates a large amount of charge and the simulation seems to over predict the charge collection efficiency. This indicates that some type of non modelled degradation of the charge transport efficiency exists, like the plasma effect where the plasma might shield the generated charges from the electric field and hence distorts the charge transport process. Based on the simulations it can be reasoned that saturation of the amplifiers in the Timepix system might generate crosstalk that increases the charge spread measured from ion impact on the sensor.

Measuring scatter radiation in diagnostic X rays for radiation protection purposes.

During the last decades, radiation protection and dosimetry in medical X-ray imaging practice has been extensively studied. The purpose of this study was to measure secondary radiation in a conventional radiographic room, in terms of ambient dose rate equivalent H*(10) and its dependence on the radiographic exposure parameters such as X-ray tube voltage, tube current and distance. With some exceptions, the results indicated that the scattered radiation was uniform in the space around the water cylindrical phantom. The results also showed that the tube voltage and filtration affect the dose rate due to the scatter radiation. Finally, the scattered X-ray energy distribution was experimentally calculated.

Active contours with prior corner detection to extract discontinuous boundaries of anatomical structures in X‐ray images

Active contours are a form of curves that deforms according to an energy minimising function and are widely used in computer vision and image processing applications to extract features of interests from raw images acquired using an image capturing device. One of the major limitations in active contours is its inability to converge accurately when the object of interest exhibits sharp corners. In this study, a new technique of active contour model to extract boundaries of objects having sharp corners is presented. By incorporating a priori knowledge of significant corners of the object into the deforming contour, the proposed active contour is able to deform towards the boundaries of the object without surpassing the corners. The ability of the new technique to accurately extract features of interest of anatomical structures in medical X-ray images having sharp corners is demonstrated.