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Fulltext Limited Evaluation of Image Quality Produced by a Portable Head CT Scanner (CereTom) in a Neurosurgery Centre

Abdullah AC, Adnan JS, Rahman NA, Palur R

Malays J Med Sci, 2017 Mar;24(1):104-112.
PMID: 28381933 DOI: 10.21315/mjms2017.24.1.11

INTRODUCTION: Computed tomography (CT) is the preferred diagnostic toolkit for head and brain imaging of head injury. A recent development is the invention of a portable CT scanner that can be beneficial from a clinical point of view.
AIM: To compare the quality of CT brain images produced by a fixed CT scanner and a portable CT scanner (CereTom).
METHODS: This work was a single-centre retrospective study of CT brain images from 112 neurosurgical patients. Hounsfield units (HUs) of the images from CereTom were measured for air, water and bone. Three assessors independently evaluated the images from the fixed CT scanner and CereTom. Streak artefacts, visualisation of lesions and grey-white matter differentiation were evaluated at three different levels (centrum semiovale, basal ganglia and middle cerebellar peduncles). Each evaluation was scored 1 (poor), 2 (average) or 3 (good) and summed up to form an ordinal reading of 3 to 9.
RESULTS: HUs for air, water and bone from CereTom were within the recommended value by the American College of Radiology (ACR). Streak artefact evaluation scores for the fixed CT scanner was 8.54 versus 7.46 (Z = -5.67) for CereTom at the centrum semiovale, 8.38 (SD = 1.12) versus 7.32 (SD = 1.63) at the basal ganglia and 8.21 (SD = 1.30) versus 6.97 (SD = 2.77) at the middle cerebellar peduncles. Grey-white matter differentiation showed scores of 8.27 (SD = 1.04) versus 7.21 (SD = 1.41) at the centrum semiovale, 8.26 (SD = 1.07) versus 7.00 (SD = 1.47) at the basal ganglia and 8.38 (SD = 1.11) versus 6.74 (SD = 1.55) at the middle cerebellar peduncles. Visualisation of lesions showed scores of 8.86 versus 8.21 (Z = -4.24) at the centrum semiovale, 8.93 versus 8.18 (Z = -5.32) at the basal ganglia and 8.79 versus 8.06 (Z = -4.93) at the middle cerebellar peduncles. All results were significant with P-value < 0.01.
CONCLUSIONS: Results of the study showed a significant difference in image quality produced by the fixed CT scanner and CereTom, with the latter being more inferior than the former. However, HUs of the images produced by CereTom do fulfil the recommendation of the ACR.

Matched MeSH terms: Artifacts
Fulltext Using 21st-Century Technologies to Determine the Cognitive Capabilities of a 11,000-Year-Old Perak Man Who Had Brachymesophalangia Type A2

Abdullah JY, Saidin M, Rajion ZA, Hadi H, Mohamad N, Moraes C, et al.

Malays J Med Sci, 2021 Feb;28(1):1-8.
PMID: 33679214 DOI: 10.21315/mjms2021.28.1.1

Perak Man, named after the state where the skeleton was found, was the most complete skeleton found in Southeast Asia. The funerary artefacts indicate that Perak Man was highly respected, as he was buried at the centre of the highest cave in Lenggong, and he was the only person buried there. A copy of the original skull was made using computed tomography (CT) and 3D printing. Based on the internal structure of the reconstructed skull, the estimated intracranial volume (ICV) is 1,204.91 mL. The hypothetical face of Perak Man was reconstructed according to established forensic methods. Based on his presumed status, Perak Man was likely a respected person in the group and, perhaps, a shaman and the most knowledgeable person in the group regarding survival, hunting, gathering and other aspects of Palaeolithic daily life.

Matched MeSH terms: Artifacts
Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals

Acharya UR, Oh SL, Hagiwara Y, Tan JH, Adeli H

Comput Biol Med, 2018 09 01;100:270-278.
PMID: 28974302 DOI: 10.1016/j.compbiomed.2017.09.017

An encephalogram (EEG) is a commonly used ancillary test to aide in the diagnosis of epilepsy. The EEG signal contains information about the electrical activity of the brain. Traditionally, neurologists employ direct visual inspection to identify epileptiform abnormalities. This technique can be time-consuming, limited by technical artifact, provides variable results secondary to reader expertise level, and is limited in identifying abnormalities. Therefore, it is essential to develop a computer-aided diagnosis (CAD) system to automatically distinguish the class of these EEG signals using machine learning techniques. This is the first study to employ the convolutional neural network (CNN) for analysis of EEG signals. In this work, a 13-layer deep convolutional neural network (CNN) algorithm is implemented to detect normal, preictal, and seizure classes. The proposed technique achieved an accuracy, specificity, and sensitivity of 88.67%, 90.00% and 95.00%, respectively.

Matched MeSH terms: Artifacts
Fulltext Physiological uptake in FDG PET simulating disease

Ahmad Sarji S

Biomed Imaging Interv J, 2006 Oct;2(4):e59.
PMID: 21614339 MyJurnal DOI: 10.2349/biij.2.4.e59

Many potential pitfalls and artefacts have been described in PET imaging that uses F-18 fluorodeoxyglucose (FDG). Normal uptake of FDG occurs in many sites of the body and may cause confusion in interpretation particularly in oncology imaging. Clinical correlation, awareness of the areas of normal uptake of FDG in the body and knowledge of variation in uptake as well as benign processes that are FDG avid are necessary to avoid potential pitfalls in image interpretation. In this context, optimum preparation of patients for their scans can be instituted in an attempt to reduce the problem. Many of the problems and pitfalls associated with areas of normal uptake of FDG can be solved by using PET CT imaging. PET CT imaging has the ability to correctly attribute FDG activity to a structurally normal organ on CT. However, the development of combined PET CT scanners also comes with its own specific problems related to the combined PET CT technique. These include misregistration artefacts due to respiration and the presence of high density substances which may lead to artefactual overestimation of activity if CT data are used for attenuation correction.

Matched MeSH terms: Artifacts
Analyzing Data Remnant Remains on User Devices to Determine Probative Artifacts in Cloud Environment

Ahmed AA, Xue Li C

J Forensic Sci, 2018 Jan;63(1):112-121.
PMID: 28397244 DOI: 10.1111/1556-4029.13506

Cloud storage service allows users to store their data online, so that they can remotely access, maintain, manage, and back up data from anywhere via the Internet. Although helpful, this storage creates a challenge to digital forensic investigators and practitioners in collecting, identifying, acquiring, and preserving evidential data. This study proposes an investigation scheme for analyzing data remnants and determining probative artifacts in a cloud environment. Using pCloud as a case study, this research collected the data remnants available on end-user device storage following the storing, uploading, and accessing of data in the cloud storage. Data remnants are collected from several sources, including client software files, directory listing, prefetch, registry, network PCAP, browser, and memory and link files. Results demonstrate that the collected remnants data are beneficial in determining a sufficient number of artifacts about the investigated cybercrime.

Matched MeSH terms: Artifacts
A review of common beam hardening correction methods for industrial x-ray computed tomography

Ahmed O, Yushou Song

Sains Malaysiana, 2018;47:1883-1890.

X-ray computed tomography (XCT) became an important instrument for quality assurance in industry products as a
non-destructive testing tool for inspection, evaluation, analysis and dimensional metrology. Thus, a high-quality image
is required. Due to the polychromatic nature of X-ray energy in XCT, this leads to errors in attenuation coefficient
which is generally known as beam hardening artifact. This leads to a distortion or blurring-like cupping and streak in
the reconstruction images, where a significant decrease in imaging quality is observed. In this paper, recent research
publications regarding common practical correction methods that were adopted to improve an imaging quality have been
discussed. It was observed from the discussion and evaluation, that a problem behind beam hardening reduction for the
multi-materials object, especially in the absence of prior information about X-ray spectrum and material characterizations
would be a significant research contribution, if the correction could be achieved without the need to perform forward
projections and multiple reconstructions.

Matched MeSH terms: Artifacts
Fulltext Mandibular Canal Enlargement: Clinical and Radiological Characteristics

Ai CJ, Jabar NA, Lan TH, Ramli R

J Clin Imaging Sci, 2017;7:28.
PMID: 28781925 DOI: 10.4103/jcis.JCIS_28_17

Enlargement of the mandibular canal is a rare radiological finding. Clinically, it may or may not be associated with sensory deficits. We report four cases of widening of the mandibular canal observed with various methods of imaging with different clinical characteristics. We describe this unique radiological finding and elaborate the importance of quality assessment of the imaging that is vital for accurate diagnosis and treatment planning. Clinicians should be mindful when assessing the imaging whenever the size of the mandibular canal is implicated. The case ranged from a benign tumor to malignancy, radiological errors, and artifacts. A more superior imaging or treatment modality was necessary to ascertain the diagnosis.

Matched MeSH terms: Artifacts
A knowledge interaction learning for multi-echo MRI motion artifact correction towards better enhancement of SWI

Al-Masni MA, Lee S, Al-Shamiri AK, Gho SM, Choi YH, Kim DH

Comput Biol Med, 2023 Feb;153:106553.
PMID: 36641933 DOI: 10.1016/j.compbiomed.2023.106553

Patient movement during Magnetic Resonance Imaging (MRI) scan can cause severe degradation of image quality. In Susceptibility Weighted Imaging (SWI), several echoes are typically measured during a single repetition period, where the earliest echoes show less contrast between various tissues, while the later echoes are more susceptible to artifacts and signal dropout. In this paper, we propose a knowledge interaction paradigm that jointly learns feature details from multiple distorted echoes by sharing their knowledge with unified training parameters, thereby simultaneously reducing motion artifacts of all echoes. This is accomplished by developing a new scheme that boosts a Single Encoder with Multiple Decoders (SEMD), which assures that the generated features not only get fused but also learned together. We called the proposed method Knowledge Interaction Learning between Multi-Echo data (KIL-ME-based SEMD). The proposed KIL-ME-based SEMD allows to share information and gain an understanding of the correlations between the multiple echoes. The main purpose of this work is to correct the motion artifacts and maintain image quality and structure details of all motion-corrupted echoes towards generating high-resolution susceptibility enhanced contrast images, i.e., SWI, using a weighted average of multi-echo motion-corrected acquisitions. We also compare various potential strategies that might be used to address the problem of reducing artifacts in multi-echoes data. The experimental results demonstrate the feasibility and effectiveness of the proposed method, reducing the severity of motion artifacts and improving the overall clinical image quality of all echoes with their associated SWI maps. Significant improvement of image quality is observed using both motion-simulated test data and actual volunteer data with various motion severity strengths. Eventually, by enhancing the overall image quality, the proposed network can increase the effectiveness of the physicians' capability to evaluate and correctly diagnose brain MR images.

Matched MeSH terms: Artifacts*
Fulltext Automatic Artifact Removal in EEG of Normal and Demented Individuals Using ICA-WT during Working Memory Tasks

Al-Qazzaz NK, Hamid Bin Mohd Ali S, Ahmad SA, Islam MS, Escudero J

Sensors (Basel), 2017 Jun 08;17(6).
PMID: 28594352 DOI: 10.3390/s17061326

Characterizing dementia is a global challenge in supporting personalized health care. The electroencephalogram (EEG) is a promising tool to support the diagnosis and evaluation of abnormalities in the human brain. The EEG sensors record the brain activity directly with excellent time resolution. In this study, EEG sensor with 19 electrodes were used to test the background activities of the brains of five vascular dementia (VaD), 15 stroke-related patients with mild cognitive impairment (MCI), and 15 healthy subjects during a working memory (WM) task. The objective of this study is twofold. First, it aims to enhance the recorded EEG signals using a novel technique that combines automatic independent component analysis (AICA) and wavelet transform (WT), that is, the AICA-WT technique; second, it aims to extract and investigate the spectral features that characterize the post-stroke dementia patients compared to the control subjects. The proposed AICA-WT technique is a four-stage approach. In the first stage, the independent components (ICs) were estimated. In the second stage, three-step artifact identification metrics were applied to detect the artifactual components. The components identified as artifacts were marked as critical and denoised through DWT in the third stage. In the fourth stage, the corrected ICs were reconstructed to obtain artifact-free EEG signals. The performance of the proposed AICA-WT technique was compared with those of two other techniques based on AICA and WT denoising methods using cross-correlation X C o r r and peak signal to noise ratio ( P S N R ) (ANOVA, p ˂ 0.05). The AICA-WT technique exhibited the best artifact removal performance. The assumption that there would be a deceleration of EEG dominant frequencies in VaD and MCI patients compared with control subjects was assessed with AICA-WT (ANOVA, p ˂ 0.05). Therefore, this study may provide information on post-stroke dementia particularly VaD and stroke-related MCI patients through spectral analysis of EEG background activities that can help to provide useful diagnostic indexes by using EEG signal processing.

Matched MeSH terms: Artifacts
Fulltext A New Diagnostic Approach in the Detection of Breast Carcinoma: Electrical Impedance Measurement with TransScan TS 2000

Amran, A.R., Fatimah, M.

International Medical Journal Malaysia, 2007;6(2):1-11.
MyJurnal

Introduction: Mammography is commonly regarded as the single most important tool for screening and for early detection of breast cancer. However it is not generally recommended for women under 40 years of age and in those taking hormone replacement therapy as the increased density of the breast parenchyma may make mammography more difficult to read and interpret. The limitations of mammography have spurred attempts to find new techniques that can be used either separately or in conjunction with mammography. Purpose: The aim of this study was to quantify the clinical value of using electrical impedance scanning (EIS) or Trans Scan as an adjunct to mammography in order to identify cancerous tissue based upon its inherent altered local dielectric properties. Methods and Materials: The patients were examined using Trans Scan (Trans Scan Medical, Ltd., distributed by Siemens AG. The study population was derived from patients with suspicious breast lesions categorized as BIRADS 3 or 4 detected during mammography or ultrasound. Results: Fifty-three women with 53 mammographically and/or sonographically suspicious findings were examined using EIS. With respect to the histopathological findings (15 malignant and 38 benign lesions) 13 of 15 (86.6% sensitivity) malignant lesions were correctly identified using EIS whereas, 33 of 38 (81.5% specificity) benign lesions were correctly identified. Negative and positive predictive values of 93.9% and 65% were observed respectively. Two benign lesions were correctly identified in a dense breast. The smallest lesion detected in this study measured 20 x 14 mm, which was an infiltrating ductal carcinoma. Conclusion: Electrical impedance scanning as an adjunct to mammography or ultrasound in classifying suspicious lesions is promising because it increases the sensitivity for cancer detection and may reduce biopsy of equivocal lesions. The additional use of EIS with negative predictive value of 93.9% may be useful to exclude some benign lesions from further diagnostic or invasive procedures. Artifacts, such as signals from superficial skin lesions, poor contact and bubbles are currently a limitation

Matched MeSH terms: Artifacts
A study on discrete wavelet-based noise removal from EEG signals

Asaduzzaman K, Reaz MB, Mohd-Yasin F, Sim KS, Hussain MS

Adv Exp Med Biol, 2010;680:593-9.
PMID: 20865544 DOI: 10.1007/978-1-4419-5913-3_65

Electroencephalogram (EEG) serves as an extremely valuable tool for clinicians and researchers to study the activity of the brain in a non-invasive manner. It has long been used for the diagnosis of various central nervous system disorders like seizures, epilepsy, and brain damage and for categorizing sleep stages in patients. The artifacts caused by various factors such as Electrooculogram (EOG), eye blink, and Electromyogram (EMG) in EEG signal increases the difficulty in analyzing them. Discrete wavelet transform has been applied in this research for removing noise from the EEG signal. The effectiveness of the noise removal is quantitatively measured using Root Mean Square (RMS) Difference. This paper reports on the effectiveness of wavelet transform applied to the EEG signal as a means of removing noise to retrieve important information related to both healthy and epileptic patients. Wavelet-based noise removal on the EEG signal of both healthy and epileptic subjects was performed using four discrete wavelet functions. With the appropriate choice of the wavelet function (WF), it is possible to remove noise effectively to analyze EEG significantly. Result of this study shows that WF Daubechies 8 (db8) provides the best noise removal from the raw EEG signal of healthy patients, while WF orthogonal Meyer does the same for epileptic patients. This algorithm is intended for FPGA implementation of portable biomedical equipments to detect different brain state in different circumstances.

Matched MeSH terms: Artifacts
Fulltext Monte Carlo dose calculation in dental amalgam phantom

Aziz MZ, Yusoff AL, Osman ND, Abdullah R, Rabaie NA, Salikin MS

J Med Phys, 2015 Jul-Sep;40(3):150-5.
PMID: 26500401 DOI: 10.4103/0971-6203.165080

It has become a great challenge in the modern radiation treatment to ensure the accuracy of treatment delivery in electron beam therapy. Tissue inhomogeneity has become one of the factors for accurate dose calculation, and this requires complex algorithm calculation like Monte Carlo (MC). On the other hand, computed tomography (CT) images used in treatment planning system need to be trustful as they are the input in radiotherapy treatment. However, with the presence of metal amalgam in treatment volume, the CT images input showed prominent streak artefact, thus, contributed sources of error. Hence, metal amalgam phantom often creates streak artifacts, which cause an error in the dose calculation. Thus, a streak artifact reduction technique was applied to correct the images, and as a result, better images were observed in terms of structure delineation and density assigning. Furthermore, the amalgam density data were corrected to provide amalgam voxel with accurate density value. As for the errors of dose uncertainties due to metal amalgam, they were reduced from 46% to as low as 2% at d80 (depth of the 80% dose beyond Zmax) using the presented strategies. Considering the number of vital and radiosensitive organs in the head and the neck regions, this correction strategy is suggested in reducing calculation uncertainties through MC calculation.

Matched MeSH terms: Artifacts
Fulltext Elevated mitochondrial genome variation after 50 generations of radiation exposure in a wild rodent

Baker RJ, Dickins B, Wickliffe JK, Khan FAA, Gaschak S, Makova KD, et al.

Evol Appl, 2017 09;10(8):784-791.
PMID: 29151870 DOI: 10.1111/eva.12475

Currently, the effects of chronic, continuous low dose environmental irradiation on the mitochondrial genome of resident small mammals are unknown. Using the bank vole (Myodes glareolus) as a model system, we tested the hypothesis that approximately 50 generations of exposure to the Chernobyl environment has significantly altered genetic diversity of the mitochondrial genome. Using deep sequencing, we compared mitochondrial genomes from 131 individuals from reference sites with radioactive contamination comparable to that present in northern Ukraine before the 26 April 1986 meltdown, to populations where substantial fallout was deposited following the nuclear accident. Population genetic variables revealed significant differences among populations from contaminated and uncontaminated localities. Therefore, we rejected the null hypothesis of no significant genetic effect from 50 generations of exposure to the environment created by the Chernobyl meltdown. Samples from contaminated localities exhibited significantly higher numbers of haplotypes and polymorphic loci, elevated genetic diversity, and a significantly higher average number of substitutions per site across mitochondrial gene regions. Observed genetic variation was dominated by synonymous mutations, which may indicate a history of purify selection against nonsynonymous or insertion/deletion mutations. These significant differences were not attributable to sample size artifacts. The observed increase in mitochondrial genomic diversity in voles from radioactive sites is consistent with the possibility that chronic, continuous irradiation resulting from the Chernobyl disaster has produced an accelerated mutation rate in this species over the last 25 years. Our results, being the first to demonstrate this phenomenon in a wild mammalian species, are important for understanding genetic consequences of exposure to low-dose radiation sources.

Matched MeSH terms: Artifacts
Fulltext Respiratory Motion Correction for Compressively Sampled Free Breathing Cardiac MRI Using Smoothl1-Norm Approximation

Bilal M, Shah JA, Qureshi IM, Kadir K

Int J Biomed Imaging, 2018;2018:7803067.
PMID: 29610569 DOI: 10.1155/2018/7803067

Transformed domain sparsity of Magnetic Resonance Imaging (MRI) has recently been used to reduce the acquisition time in conjunction with compressed sensing (CS) theory. Respiratory motion during MR scan results in strong blurring and ghosting artifacts in recovered MR images. To improve the quality of the recovered images, motion needs to be estimated and corrected. In this article, a two-step approach is proposed for the recovery of cardiac MR images in the presence of free breathing motion. In the first step, compressively sampled MR images are recovered by solving an optimization problem using gradient descent algorithm. TheL1-norm based regularizer, used in optimization problem, is approximated by a hyperbolic tangent function. In the second step, a block matching algorithm, known as Adaptive Rood Pattern Search (ARPS), is exploited to estimate and correct respiratory motion among the recovered images. The framework is tested for free breathing simulated andin vivo2D cardiac cine MRI data. Simulation results show improved structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), and mean square error (MSE) with different acceleration factors for the proposed method. Experimental results also provide a comparison betweenk-tFOCUSS with MEMC and the proposed method.

Matched MeSH terms: Artifacts
Fulltext Reduction of Motion Artifacts in the Recovery of Undersampled DCE MR Images Using Data Binning and L+S Decomposition

Bilal M, Anis H, Khan N, Qureshi I, Shah J, Kadir KA

Biomed Res Int, 2019;2019:6139785.
PMID: 31119178 DOI: 10.1155/2019/6139785

Background: Motion is a major source of blurring and ghosting in recovered MR images. It is more challenging in Dynamic Contrast Enhancement (DCE) MRI because motion effects and rapid intensity changes in contrast agent are difficult to distinguish from each other.
Material and Methods: In this study, we have introduced a new technique to reduce the motion artifacts, based on data binning and low rank plus sparse (L+S) reconstruction method for DCE MRI. For Data binning, radial k-space data is acquired continuously using the golden-angle radial sampling pattern and grouped into various motion states or bins. The respiratory signal for binning is extracted directly from radially acquired k-space data. A compressed sensing- (CS-) based L+S matrix decomposition model is then used to reconstruct motion sorted DCE MR images. Undersampled free breathing 3D liver and abdominal DCE MR data sets are used to validate the proposed technique.
Results: The performance of the technique is compared with conventional L+S decomposition qualitatively along with the image sharpness and structural similarity index. Recovered images are visually sharper and have better similarity with reference images.
Conclusion: L+S decomposition provides improved MR images with data binning as preprocessing step in free breathing scenario. Data binning resolves the respiratory motion by dividing different respiratory positions in multiple bins. It also differentiates the respiratory motion and contrast agent (CA) variations. MR images recovered for each bin are better as compared to the method without data binning.

Matched MeSH terms: Artifacts
An Evidence-based Forensic Taxonomy of Windows Phone Dating Apps

Cahyani NDW, Choo KR, Ab Rahman NH, Ashman H

J Forensic Sci, 2019 Jan;64(1):243-253.
PMID: 29783278 DOI: 10.1111/1556-4029.13820

Advances in technologies including development of smartphone features have contributed to the growth of mobile applications, including dating apps. However, online dating services can be misused. To support law enforcement investigations, a forensic taxonomy that provides a systematic classification of forensic artifacts from Windows Phone 8 (WP8) dating apps is presented in this study. The taxonomy has three categories, namely: Apps Categories, Artifacts Categories, and Data Partition Categories. This taxonomy is built based on the findings from a case study of 28 mobile dating apps, using mobile forensic tools. The dating app taxonomy can be used to inform future studies of dating and related apps, such as those from Android and iOS platforms.

Matched MeSH terms: Artifacts
An Evidence-Based Forensic Taxonomy of Windows Phone Communication Apps

Cahyani NDW, Martini B, Choo KR, Ab Rahman NH, Ashman H

J Forensic Sci, 2018 May;63(3):868-881.
PMID: 28833117 DOI: 10.1111/1556-4029.13624

Communication apps can be an important source of evidence in a forensic investigation (e.g., in the investigation of a drug trafficking or terrorism case where the communications apps were used by the accused persons during the transactions or planning activities). This study presents the first evidence-based forensic taxonomy of Windows Phone communication apps, using an existing two-dimensional Android forensic taxonomy as a baseline. Specifically, 30 Windows Phone communication apps, including Instant Messaging (IM) and Voice over IP (VoIP) apps, are examined. Artifacts extracted using physical acquisition are analyzed, and seven digital evidence objects of forensic interest are identified, namely: Call Log, Chats, Contacts, Locations, Installed Applications, SMSs and User Accounts. Findings from this study would help to facilitate timely and effective forensic investigations involving Windows Phone communication apps.

Matched MeSH terms: Artifacts
Fulltext An artifacts removal post-processing for epiphyseal region-of-interest (EROI) localization in automated bone age assessment (BAA)

Chai HY, Wee LK, Swee TT, Salleh ShH, Chea LY

Biomed Eng Online, 2011;10:87.
PMID: 21952080 DOI: 10.1186/1475-925X-10-87

Segmentation is the most crucial part in the computer-aided bone age assessment. A well-known type of segmentation performed in the system is adaptive segmentation. While providing better result than global thresholding method, the adaptive segmentation produces a lot of unwanted noise that could affect the latter process of epiphysis extraction.

Matched MeSH terms: Artifacts*
Fulltext The resin-embedded cornea prepared via rapid processing protocol : a good histomorphometric target for clinical investigation in ophthalmology and optometry

Cheah PS, Mohidin N, Mohd Ali B, Maung M, Latif AA

Malays J Med Sci, 2008 Jul;15(3):49-54.
PMID: 22570589

This study illustrates and quantifies the changes on corneal tissue between the paraffin-embedded and resin-embedded blocks and thus, selects a better target in investigational ophthalmology and optometry via light microscopy. Corneas of two cynomolgus monkeys (Macaca fascicularis) were used in this study. The formalin-fixed cornea was prepared in paraffin block via the conventional tissue processing protocol (4-day protocol) and stained with haematoxylin and eosin. The glutaraldehyde-fixed cornea was prepared in resin block via the rapid and modified tissue processing procedure (1.2-day protocol) and stained with toluidine blue. The paraffin-embedded sample exhibits various undesired tissue damage and artifact such as thinner epithelium (due to the substantial volumic extraction from the tissue), thicker stroma layer (due to the separation of lamellae and the presence of voids) and the distorted endothelium. In contrast, the resin-embedded corneal tissue has demonstrated satisfactory corneal ultrastructural preservation. The rapid and modified tissue processing method for preparing the resin-embedded is particularly beneficial to accelerate the microscopic evaluation in ophthalmology and optometry.

Matched MeSH terms: Artifacts
Correlation between subjective and objective assessment of magnetic resonance (MR) images

Chow LS, Rajagopal H, Paramesran R, Alzheimer's Disease Neuroimaging Initiative

Magn Reson Imaging, 2016 07;34(6):820-831.
PMID: 26969762 DOI: 10.1016/j.mri.2016.03.006

Medical Image Quality Assessment (IQA) plays an important role in assisting and evaluating the development of any new hardware, imaging sequences, pre-processing or post-processing algorithms. We have performed a quantitative analysis of the correlation between subjective and objective Full Reference - IQA (FR-IQA) on Magnetic Resonance (MR) images of the human brain, spine, knee and abdomen. We have created a MR image database that consists of 25 original reference images and 750 distorted images. The reference images were distorted with six types of distortions: Rician Noise, Gaussian White Noise, Gaussian Blur, DCT compression, JPEG compression and JPEG2000 compression, at various levels of distortion. Twenty eight subjects were chosen to evaluate the images resulting in a total of 21,700 human evaluations. The raw scores were then converted to Difference Mean Opinion Score (DMOS). Thirteen objective FR-IQA metrics were used to determine the validity of the subjective DMOS. The results indicate a high correlation between the subjective and objective assessment of the MR images. The Noise Quality Measurement (NQM) has the highest correlation with DMOS, where the mean Pearson Linear Correlation Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) are 0.936 and 0.938 respectively. The Universal Quality Index (UQI) has the lowest correlation with DMOS, where the mean PLCC and SROCC are 0.807 and 0.815 respectively. Student's T-test was used to find the difference in performance of FR-IQA across different types of distortion. The superior IQAs tested statistically are UQI for Rician noise images, Visual Information Fidelity (VIF) for Gaussian blur images, NQM for both DCT and JPEG compressed images, Peak Signal-to-Noise Ratio (PSNR) for JPEG2000 compressed images.

Matched MeSH terms: Artifacts

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