Quality Of Medical Images Research Articles

The Architectural Design of Deblocking Filter for Image Enhancement in the Diagnosis of Cancer

Objective:This method is to reduce the risk of imprecise diagnosis associated with poor-quality CT images, this paper presents a new technique designed to enhance the quality of medical CT images. The main objective is to improve the appearance of CT images in order to obtain better visual interpretation and analysis, which is expected to ease the diagnosis process. The proposed technique involves applying a deblocking filter is to enhance the visual nature of a picture by diminishing the blocking artifacts. The appearance of a picture isn’t clear while an antique happens. The proposed deblocking filter calculation gives a strategy to expel the ancient rarities by smoothing the sharp edges of a picture.Methods:With a specific goal to lessen the quantity of information access, multifaceted nature and consequently to upgrade the proficiency, a six-staged pipelined structure for picture pixels are proposed. Besides, to enhance the subjective and target nature of a picture the deblocking filter performs identification of the antique at the coded square limits and weakens them by applying a chose filter.Result:The proposed algorithm is implemented in HDL using Xilinx FPGA. The input image is converted into decimal pixel values using Matlab and this value is used as the input in HDL. The proposed algorithm is compared with other blocking algorithms.Conclusion:To design an effective deblocking filter with low cost, low complexity and high intensity, pipeline based systems are used. In addition to that the number of memory accesses and timing efficiency also be reduced using this method. The deblocking filtering operations can also easily perform in parallel on multiple processors by using six-stage of pipelined, two-line deblocking filter. The parameter mean, variance, standard deviation, resolution, contrast and PSNR values are compared with the previous method. Hence it shows the implementation of deblocking filter using pipelining is more efficient than others.

Standardization of Analysis Conditions and Prediction of Increase Prediction Using Blood Flow Analysis Software for Cerebral Aneurysms: Phantom Study and Clinical Study

In recent years, reports have been made that predict the state of aneurysm by performing computational fluid dynamics (CFD) analysis using cerebral aneurysm blood flow analysis software. However, analysis results are not constant and there are various opinions, and it is conceivable that the image quality and analysis conditions of medical images used for CFD analysis are not standardized. In this study, CFD analysis of cerebral aneurysm phantom was performed, and image quality and analysis conditions were standardized. Then, we investigated whether increase of cerebral aneurysm and prediction of rupture are possible. From this study, stable results of wall shear stress analysis were obtained under slice thickness 1.0 mm or less, CT value 400 HU or more, reconstruction function as soft part function, image SD under 10 HU. In addition, as the size of the cerebral aneurysm became larger, wall shear stress tended to be lower, and the same tendency was shown also in clinical cases. Although CFD analysis using software dedicated to blood flow analysis did not reach the prediction of rupture, it can be evaluated based on the quantitative values for the aneurysm increase at the preceding stage and plays an important role in prediction there is a possibility.

Can Signal-to-Noise Ratio Perform as a Baseline Indicator for Medical Image Quality Assessment

Natural image quality assessment (NIQA) wins increasing attention, while NIQA models are rarely used in the medical community. A couple of studies employ the NIQA methodologies for medical image quality assessment (MIQA), but building the benchmark data sets necessitates considerable time and professional skills. In particular, the characteristics of synthesized distortions are different from those of clinical distortions, which make the results not so convincing. In clinic, signal-to-noise ratio (SNR) is widely used, which is defined as the quotient of the mean signal intensity measured in a tissue region of interest (ROI) and the standard deviation of the signal intensity in an air region outside the imaged object, and both regions are outlined by specialists. We take advantage of the knowledge that SNR is routinely used and concern whether SNR measure can perform as a baseline metric for the development of MIQA algorithms. To address the issue, the inter-observer reliability of SNR measure is investigated regarding to different tissue ROIs [white matter (WM); cerebral spinal fluid (CSF)] in magnetic resonance (MR) images. A total of 192 T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> , 88 T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> , 76 T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> and 55 contrast-enhanced T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> (T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> C) weighted images are analyzed. Statistical analysis indicates that SNR values show consistency between different observers to the same ROI in each modality (Wilcoxon rank sum test, p <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">w</sub> ≥ 0.11; and paired sample t-test, pp 0.28). Moreover, whether off-the-shelf NIQA models can predict MR image quality is considered by using SNR values as the reference scores. Four NIQA models (BIQI, BLIINDS-II, BRISQUE, and NIQE) are evaluated, and the correlation between SNR values and NIQA results is evaluated. Pearson correlation coefficient (r <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> ) shows that WM-based SNR values correlates well with BIQI, BLIINDS-II and BRISQUE in T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">*</sup> images (rp 0.77), BRISQUE and NIQE in T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> images (r <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> ≥ 0.75), BLIINDS-II in T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> images (rp 0.67), and BRISQUE and NIQE in T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> C images (r <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> ≥ 0.58), while CSF-based SNR values correlates well with BLIINDS-II in T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">*</sup> images (r <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> ≥ 0.64) and T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> images (r <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> ≥ 0.60), and all p <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sub> <; 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-4</sup> . The prediction performance analysis further proves the result from the correlation analysis. Conclusively, SNR measure is reliable to different observations and can perform as a baseline indicator for the development of MIQA algorithms. In general, BRISQUE and BLIINDS-II are full of potential to be conditionally used as objective MIQA models toward human brain MR images. This paper presents the first attempt of using SNR measure to bridge the gap between NIQA and MIQA, and large-scale experiments should be further conducted to confirm the conclusion in this paper.

Object Contour in Low Quality Medical Images in Curvelet Domain

The diagnosis and treatment are very important for extending the life of patients. The small abnormalities may also be manifestations of the diseases. One of the abnormalities is the contour of each object in medical images. Therefore, the contour is very important and special to low quality medical images. In this paper, we propose a new method to detect the object contour of low quality medical images based on the self affine snake, one of the types of active contour models. The method includes two periods. Firstly, we use augmented lagrangian method to remove noise and detect edges in low quality medical images in curvelet domain. Finally, the active contour model is improved to show the contour of objects. After comparing the appearance of the contour and the time processing with other algorithms, we confirm that the proposed method is better.

The Effects of Image Quality due to Scattering X-ray according to increasing Patient Thickness

In this study, scattering factors affecting the quality of medical images were quantitatively analyzed and investigated. MCNPX simulation was conducted by using ANSI phantom, made of tissue equivalent materials, to calculate the scattering ratio occurred by the increase of the object thickness. Then, the result of the simulation was compared with the result of actual radiation measurement. In addition, we evaluated the image quality by the RMS evaluation, RSD and NPS analysis using X-ray images acquired with increasing object thickness. Furthermore, the scattering ratio was analyzed by increasing the thickness of acrylic phantom on chest phantom. The result showed that the scattering ratio was increased to 57.2%, 62.4%, and 66.8% from 48.9%, respectively, when the acrylic phantom thickness was increased by 1 inch from 6.1 inches. The results of MCNPX simulation and the actual measured scattering dose showed similar results. Also, as a result of RMS measurement from acquired x-ray images, the standard deviation decreased as the object thickness increased. However, in the RSD analysis considering the average incident dose, the results were increased from 0.028 to 0.039, 0.051, 0.062 as the acrylic phantom thickness was increased from 6.1 inches to 7.1 inch, 8.1 inch, and 9.1 inch, respectively. It can be seen that the increase of the scattering effect due to the increase of the object thickness reduces the SNR. Also, the NPS results obtained by measuring scattered radiation incident on the detector resulted in the increase of the noise as the object thickness increased.

Performance Comparison of Tetrolet Transform and Wavelet-Based Transforms for Medical Image Denoising

Noise reduces the quality of medical images and raise the difficulties of diagnosis. Although the wavelet transform has already been used in medical noise removal applications extensively, there are many other multi-resolution analysis methods proposed in recent years for denoising. The main goal of this study is comparing the image denoising abilities of some of these methods with wavelet transform. In this paper, image denoising is implemented by a three-stage methodology. Effectiveness of the multiresolution analysis methodologies has been investigated for standard test images beside magnetic resonans, mammography and fundus images. Performances of the transforms are compared by using peak signal to noise ratio, mean square error, mean structural similarity index and feature similarity index. The best results are obtained by tetrolet transform for random and rician noise with the benchmark images. Medical image denoising performance of Tetrolet transform is compared to other multiresolution analysis methods for the first time in the literature with this study. It surpassed ridgelet and haar wavelet transforms while the noise ratio was low. On the other hand, it is seen that curvelet transforms are effectively produce the best results for all rates of noise on medical images.

Performance of image transmission over MC-CDMA based on super resolution technique

Multi-carrier code-division-multiple-access (MC-CDMA) is a promising technique to obtain high data rate in wireless communication. Contemplation of medical image transmission for various patient’s information using MC-CDMA system through wireless media is discussed. Arnold cat map encryption algorithm is ensured to enhance the image transmission securely. At each mobile station, transmitted bit stream of encrypted images is estimated using minimum-mean-square error (MMSE) algorithm. The picture quality is ensured at the receiver by adopting super resolution through sparse technique. The performance of considered system through stanford channel model specification is illustrated. PSNR metric is also considered for image transmission. From the analysis, it is observed that considered MC-CDMA system with encryption algorithm and sparse based super resolution technique mitigates multi-user interference effects while retaining the quality of individual medical images. Further, it is witnessed that the channel encoded proposed system’s performance achieves the promising bit-error-rate for MMSE receiver. Furthermore, from the simulation it is discerned that the computational time for super resolution is minimized using considered sparse technique.

A Low Cost Image De-noising Implementation Using Low Area CSLA for Impulse Noise Removal

In the process of image acquisition and transmission, data can be corrupted by impulse noise. This paper presented the removal of impulse noise in medical image by using Very Large Scale Integrated circuit (VLSI) implementation. The Low Cost Reduced Simple Edge Preserved De-noising (LCRSEPD) technique is introduced using Low Area Carry Select Adder (CSLA) to remove the salt and pepper noise instead of normal adder. Thus, LCRSEPD technique preserves visual performance and edge features in terms of quality and quantitative evaluation. By optimizing the architecture, low cost RSEPD can achieve low computational complexity that will reflect in area, power and delay. Compared to the previous VLSI implementations, the LCRSEPD implementation with CSLA adder has achieved good medical image quality and less hardware cost due to the reduction of area, power and delay.

Quality assessment for wireless capsule endoscopy videos compressed via HEVC: From diagnostic quality to visual perception

Maintaining the quality of medical images and videos is an essential part of the e-services provided by the healthcare sector. The convergence of modern communication systems and the healthcare industry necessitates the provision of better quality of service and experience by the service provider. Recent inclusion and standardization of the high efficiency video coder (HEVC) has made it possible for medical data to be compressed and transmitted over wireless networks with minimal compromise of the quality. Quality evaluation and assessment of these medical videos transmitted over wireless networks is another important research area that requires further exploration and attention. In this paper, we have conducted an in-depth study of video quality assessment for compressed wireless capsule endoscopy (WCE) videos. Our study includes the performance evaluation of several state-of-the-art objective video quality metrics in terms of determining the quality of compressed WCE videos. Subjective video quality experiments were conducted with the assistance of experts and non-experts in order to predict the diagnostic and visual quality of these medical videos, respectively. The evaluation of the metrics is based on three major performance metrics that include, correlation between the subjective and objective scores, relative statistical performance and computation time. Results show that the metrics information fidelity criterion (IFC), visual information fidelity-(VIF) and especially pixel based VIF stand out as best performing metrics. Furthermore, our paper reports the performance of HEVC compression on medical videos and according to the results, it performs optimally in preserving the diagnostic and visual quality of WCE videos at Quantization Parameter (QP) values of up to 35 and 37 respectively.

Edge Detection on Objects of Medical Image with Enhancement Multiple Morphological Gradient Method

Medical image is an invaluable tool in the detection of diseases or abnormalities in human organs. The low quality of medical images cause difficulty in observing the objects contained in the image, causing errors in detection. This research develops a method for improving the quality of medical images so that the edges of objects more clearly. This method is called Enhancement multiple Morphological Gradient Enhancement (EmMG). The method used at medical images had different formats, that as Computed Tomography Scan (CT-Scan) with format type Windows bitmap (bmp), Chest X-Ray with format type Joint Photographic Experts Group (jpg) and Panoramic X-Ray with format type Portable Network Graphics (png). The method developed produces images that can further clarify the edge of the object in the medical image, making it easier to detect diseases or abnormalities in the human body. This method can used as one of the solutions in medical help to improve the accuracy in detecting objects in medical images because the edge of the objects seen clearly.

Physical characterization of the quality of medical images does not adequately reflect their clinical quality.

Quality assurance for radiological imaging equipment typically consists of analyzing data on images of physical phantoms and, if the results meet certain standards, it is assumed that clinical images obtained using the equipment will automatically be of good quality. Some claim, however, that such purely physical characterization of the quality of medical images does not adequately reflect their clinical quality. This is the premise debated in this month's Point/Counterpoint. This article is protected by copyright. All rights reserved.

Alarming system in real time and high quality display using volumerendering for otologic surgical navigation: a preclinical study

Objective:The aim of this study is to design and develop a novel navigation framework that alarms the surgeon with sound during drilling and dynamically renders the high quality medical image data. Method:The accuracy of the proposed system were measured with a skull model using paired point registration and the target registration error (TRE) was computed. We segmented the accurate structure of target and compute the minimum distance between the drill tip and the target. Once the drill tip approached the target structures, the system would alarm the surgeon. We proposed a novelty method that used a mask to render the medical image data in real time. Result:The maximum distance error of 90 target points was 1.016 mm, the minimum was 0.427 mm, and the average distance error was (0.74±0.07) mm. The design and development of the alarming system and dynamically rendering the medical image data of navigation system was accomplished. Conclusion:The results show that the accuracy of the navigation system can meet the clinical needs. It also demonstrates the feasibility of the alarm system and dynamic display system and its application prospects.

Vision-Based Surgical Field Defogging.

Fogged surgical field visualization that is a common and potentially harmful problem can lead to inappropriate device use and incorrectly targeted tissue and increase surgical risks in endoscopic surgery. This paper aims to remove fog or smoke on endoscopic video sequences to augment and maintain a direct and clear visualization of the operating field. A new visibility-driven fusion defogging framework is proposed for surgical endoscopic video processing. This framework first recovers the visibility and enhances the contrast of hazy images. To address the color infidelity problem introduced by the visibility recovery, the luminances of the recovered and enhanced images are fused in the gradient domain, and the fused luminance is reconstructed by solving the Poisson equation in the frequency domain. The proposed method is evaluated on clinical videos that were collected from prostate cancer surgery. The experimental results demonstrate that the proposed framework defogs endoscopic images more robustly than currently available methods. Additionally, our method also provides an effective way to improve the visual quality of medical or high-dynamic range images.

A REVIEW PAPER ON MEDICAL IMAGE PROCESSING

Biomedical image processing has experienced dramatic expansion, and has been an interdisciplinary research field attracting expertise from applied mathematics, computer sciences, engineering, statistics, physics, biology and medicine. Computer-aided diagnostic processing has already become an important part of clinical routine. Accompanied by a rush of new development of high technology and use of various imaging modalities, more challenges arise; for example, how to process and analyze a significant volume of images so that high quality information can be produced for disease diagnoses and treatment. The principal objectives of this course are to provide an introduction to basic concepts and techniques for medical image processing and to promote interests for further study and research in medical imaging processing.The rapid progress of medical science and the invention of various medicines have benefited mankind and the whole civilization. Modern science also has been doing wonders in the surgical field. But, the proper and correct diagnosis of diseases is the primary necessity before the treatment. The more sophisticate the bio-instruments are, better diagnosis will be possible. The medical image plays an important role in clinical diagnosis and therapy of doctor and teaching and researching etc. Medical imaging is often thought of as a way to represent anatomical structures of the body with the help of X-ray computed tomography and magnetic resonance imaging. But often it is more useful for physiologic function rather than anatomy. With the growth of computer and image technology medical imaging has greatly influenced medical field. As the quality of medical imaging affects diagnosis the medical image processing has become a hotspot and the clinical applications wanting to store and retrieve images for future purpose needs some convenient process to store those images in details.

Noise indices adjusted to body mass index and an iterative reconstruction algorithm maintain image quality on low-dose contrast-enhanced liver CT.

Since body mass index (BMI) affects medical imaging quality or noise due to penetration of the radiation through bodies with varying sizes, this study aims to investigate and determine the optimal BMI-adjusted noise index (NI) setting on the contrast-enhanced liver CT scans obtained using 3D Smart mA technology with adaptive statistical iterative reconstruction (ASIR 2.0) algorithm. A total of 320 patients who had contrast-enhanced liver CT scans were divided into two equal-sized groups: A (18.5 kg/m2≤BMI<24.9 kg/m2) and B (24.9 kg/m2 ≤ BMI ≤34.9 kg/m2). The two groups were randomly divided into four subgroups with an NI of 11, 13, 15, and 17. All images were reconstructed with 50% ASIR 2.0. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated after the late arterial, portal venous, and equilibrium phases were completed. Images were evaluated by two radiologists using a subjective 0 -5 scale. Mean CT dose index of volume, dose-length product, and effective dose (ED) were calculated and compared using one-way ANOVA. In group A, the best-quality images obtained at the lowest ED were scanned at an NI of 15 in the late arterial phase, and at an NI of 17 in the portal venous and equilibrium phases. In group B, the best results were obtained at an NI of 13 in the late arterial phase, and at an NI of 15 in the portal venous and equilibrium phases. Adjusting NI and iterative reconstruction algorithm based on body mass index can help improve image quality on contrast-enhanced liver CT scans, even at low radiation dose.

The role of extra-foveal processing in 3D imaging.

The field of medical image quality has relied on the assumption that metrics of image quality for simple visual detection tasks are a reliable proxy for the more clinically realistic visual search tasks. Rank order of signal detectability across conditions often generalizes from detection to search tasks. Here, we argue that search in 3D images represents a paradigm shift in medical imaging: radiologists typically cannot exhaustively scrutinize all regions of interest with the high acuity fovea requiring detection of signals with extra-foveal areas (visual periphery) of the human retina. We hypothesize that extra-foveal processing can alter the detectability of certain types of signals in medical images with important implications for search in 3D medical images. We compare visual search of two different types of signals in 2D vs. 3D images. We show that a small microcalcification-like signal is more highly detectable than a larger mass-like signal in 2D search, but its detectability largely decreases (relative to the larger signal) in the 3D search task. Utilizing measurements of observer detectability as a function retinal eccentricity and observer eye fixations we can predict the pattern of results in the 2D and 3D search studies. Our findings: 1) suggest that observer performance findings with 2D search might not always generalize to 3D search; 2) motivate the development of a new family of model observers that take into account the inhomogeneous visual processing across the retina (foveated model observers).

Cateterismo cardiaco ambulatorio. Experiencia inicial

Development of card iovascu lar surgical techniques and more recently, baloon angioplasty, has resulted in a dramatic increase in the number of cardiac catheterizations performed.&#x0D; &#x0D; Previously, the usual policy was to admit the patient to the hospital for several days. Various series of patients submitted to ambulatory cardiac catheterizations have revealed that this procedure con be performed safely, with a potential reduction in hospital and patients costs, better utilization of medical beds and good image quality. In this study we present our initial experience in this kind of outpatient procedure.

A ROI-based high capacity reversible data hiding scheme with contrast enhancement for medical images

In this paper, we attempt to investigate the secure archiving of medical images which are stored on semi-trusted cloud servers, and focus on addressing the complicated and challenging integrity control and privacy preservation issues. With the intention of protecting the medical images stored on a semi-trusted server, a novel ROI-based high capacity reversible data hiding (RDH) scheme with contrast enhancement is proposed in this paper. The proposed method aims at improving the quality of the medical images effectively and embedding high capacity data reversibly meanwhile. Therefore, the proposed method adopts “adaptive threshold detector” (ATD) segmentation algorithm to automatically separate the “region of interest” (ROI) and “region of non-interest” (NROI) at first, then enhances the contrast of the ROI region by stretching the grayscale and embeds the data into peak bins of the stretched histogram without extending the histogram bins. Lastly, the rest of the required large of data are embedded into NROI region regardless its quality. In addition, the proposed method records the edge location of the segmentation instead of recording the location of the overflow and underflow. The experiment shows that the proposed method can improve the quality of medical images obviously whatever in low embedding rate or high embedding rate when compared with other contrast-based RDH methods.

Medical Image Steganography: Study of Medical Image Quality Degradation when Embedding Data in the Frequency Domain

Medical Image Steganography: Study of Medical Image Quality Degradation when Embedding Data in the Frequency Domain

Evaluation of 3D printing materials for fabrication of a novel multi-functional 3D thyroid phantom for medical dosimetry and image quality

Recently, the three-dimensional printer has started to be utilized strongly in medical industries. In the human body, many parts or organs can be printed from 3D images to meet accurate organ geometries.In this study, five common 3D printing materials were evaluated in terms of their elementary composition and the mass attenuation coefficients. The online version of XCOM photon cross-section database was used to obtain the attenuation values of each material. The results were compared with the attenuation values of the thyroid listed in the International Commission on Radiation Units and Measurements - ICRU 44.Two original thyroid models (hollow-inside and solid-inside) were designed from scratch to be used in nuclear medicine, diagnostic radiology and radiotherapy for dosimetry and image quality purposes. Both designs have three holes for installation of radiation dosimeters. The hollow-inside model has more two holes in the top for injection the radioactive materials.The attenuation properties of the Polylactic Acid (PLA) material showed a very good match with the thyroid tissue, which it was selected to 3D print the phantom using open source RepRap, Prusa i3 3D printer.The scintigraphy images show that the phantom simulates a real healthy thyroid gland and thus it can be used for image quality purposes. The measured CT numbers of the PA material after the 3D printing show a close match with the human thyroid CT numbers. Furthermore, the phantom shows a good accommodation of the TLD dosimeters inside the holes.The 3D fabricated thyroid phantom simulates the real shape of the human thyroid gland with a changeable geometrical shape-size feature to fit different age groups.By using 3D printing technology, the time required to fabricate the 3D phantom was considerably shortened compared to the longer conventional methods, where it took only 30min to print out the model. The 3D printing material used in this study is commercially available and cost-effective compared to current commercial tissue-equivalent materials.