MyMedR

Displaying publications 1 - 20 of 78 in total

Abstract:

Sort:

Fulltext 3D-Printed Coronary Plaques to Simulate High Calcification in the Coronary Arteries for Investigation of Blooming Artifacts

Sun Z, Ng CKC, Wong YH, Yeong CH

Biomolecules, 2021 09 03;11(9).
PMID: 34572520 DOI: 10.3390/biom11091307

The diagnostic value of coronary computed tomography angiography (CCTA) is significantly affected by high calcification in the coronary arteries owing to blooming artifacts limiting its accuracy in assessing the calcified plaques. This study aimed to simulate highly calcified plaques in 3D-printed coronary models. A combination of silicone + 32.8% calcium carbonate was found to produce 800 HU, representing extensive calcification. Six patient-specific coronary artery models were printed using the photosensitive polyurethane resin and a total of 22 calcified plaques with diameters ranging from 1 to 4 mm were inserted into different segments of these 3D-printed coronary models. The coronary models were scanned on a 192-slice CT scanner with 70 kV, pitch of 1.4, and slice thickness of 1 mm. Plaque attenuation was measured between 1100 and 1400 HU. Both maximum-intensity projection (MIP) and volume rendering (VR) images (wide and narrow window widths) were generated for measuring the diameters of these calcified plaques. An overestimation of plaque diameters was noticed on both MIP and VR images, with measurements on the MIP images close to those of the actual plaque sizes (<10% deviation), and a large measurement discrepancy observed on the VR images (up to 50% overestimation). This study proves the feasibility of simulating extensive calcification in coronary arteries using a 3D printing technique to develop calcified plaques and generate 3D-printed coronary models.

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
Fulltext A case study on culture-oriented design preferences

Wardahanisah Razali, Rusmadiah Anwar

The Pertanika Journal of Scholarly Research Reviews, 2018;4(2):64-70.
MyJurnal

It is hard to identify the local Malay identity in a design context compared to other cultural oriented design in several countries. This paper tries to uncover how designers interpret local identity embodied agent based on local items influences and understood and the influence of incremental, radical design that changes respective to preceding designs. A descriptive study through the literature reviews focusses on a type of artefact initiated through cultural-oriented design. Based on the preliminary study, a sampling taken from the Chinese, Indian, Japanese or European consistently apply the same fundamental understanding in regards to the culture-oriented design. From the same point of view, teapot seems to be used as one of the dominant artefact indicating the design preferences. This research will benefit both the academia and the industry and identify significant identity based on the local context and become an embodied agent to give impact in establishing the state-of-the-art of brand, the identity of local design, establish new trademark towards generating domestic, international economy and promote the nation worldwide throughout design platform.

Matched MeSH terms: Artifacts
A fuzzy-based texture analysis for tissue characterization of diffused liver diseases on B-scan images

Gangeh MJ, Hanmandlu M, Bister M

Biomed Sci Instrum, 2002;38:369-74.
PMID: 12085634

The specific texture on B-scan images is believed to be related to both ultrasound machine characteristics and tissue properties, i.e., the pathological states of the soft tissue. Therefore, for classification, features can be extracted with the use of image texture analysis techniques. In this paper a novel fuzzy approach for texture characterization is used for classification of normal liver and diffused liver diseases, here fatty liver, liver cirrhosis, and hepatitis are emphasized. The texture analysis techniques are diversified by the existence of several approaches. We propose fuzzy features for the analysis of the texture image. For this, a membership function is constructed to represent the effect of the neighboring pixels on the current pixel in a window. Using these membership function values, we find a feature by weighted average method for the current pixel. This is repeated for all pixels in the window treating each time one pixel as the current pixel. Using these fuzzy based features, we derive three descriptors: maximum, entropy, and energy as used in co-occurrence method, for each window.

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 A new method of mark detection for software-based optical mark recognition

Loke SC, Kasmiran KA, Haron SA

PLoS One, 2018;13(11):e0206420.
PMID: 30412588 DOI: 10.1371/journal.pone.0206420

Software optical mark recognition (SOMR) is the process whereby information entered on a survey form or questionnaire is converted using specialized software into a machine-readable format. SOMR normally requires input fields to be completely darkened, have no internal labels, or be filled with a soft pencil, otherwise mark detection will be inaccurate. Forms can also have print and scan artefacts that further increase the error rate. This article presents a new method of mark detection that improves over existing techniques based on pixel counting and simple thresholding. Its main advantage is that it can be used under a variety of conditions and yet maintain a high level of accuracy that is sufficient for scientific applications. Field testing shows no software misclassification in 5695 samples filled by trained personnel, and only two misclassifications in 6000 samples filled by untrained respondents. Sensitivity, specificity, and accuracy were 99.73%, 99.98%, and 99.94% respectively, even in the presence of print and scan artefacts, which was superior to other methods tested. A separate direct comparison for mark detection showed a sensitivity, specificity, and accuracy respectively of 99.7%, 100.0%, 100.0% (new method), 96.3%, 96.0%, 96.1% (pixel counting), and 99.9%, 99.8%, 99.8% (simple thresholding) on clean forms, and 100.0%, 99.1%, 99.3% (new method), 98.4%, 95.6%, 96.2% (pixel counting), 100.0%, 38.3%, 51.4% (simple thresholding) on forms with print artefacts. This method is designed for bubble and box fields, while other types such as handwriting fields require separate error control measures.

Matched MeSH terms: Artifacts
A pseudo-cryptococcal artefact derived from leucocytes in wet India ink mounts of centrifuged cerebrospinal fluid

Thiruchelvan N, Wuu KY, Arseculeratne SN, Ashraful-Haq J

J Clin Pathol, 1998 Mar;51(3):246-8.
PMID: 9659271

Wet India ink mounts of cerebrospinal fluid (CSF) are useful in the laboratory diagnosis of cryptococcal meningitis. Pseudo-cryptococcal artefacts in such mounts have been attributed to leucocytes in CSF but their mode of formation has not been explained. This report describes the reproduction of such an artefact in cryptococcus free CSF-leucocyte mixtures that had been subjected to high speed centrifugation. The viscosity of DNA that could provide a morphological pseudo-capsule, and the yellow-green fluorescence of the pseudo-capsular material on staining with acridine-orange, suggest that lymphocytic nuclear DNA, which possibly leaked out after damage to the lymphocyte membrane by centrifugation, was responsible for this artefact.

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
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 ARTYCUL: A Privacy-Preserving ML-Driven Framework to Determine the Popularity of a Cultural Exhibit on Display

Tanwar G, Chauhan R, Yafi E

Sensors (Basel), 2021 Feb 22;21(4).
PMID: 33671822 DOI: 10.3390/s21041527

We present ARTYCUL (ARTifact popularitY for CULtural heritage), a machine learning(ML)-based framework that graphically represents the footfall around an artifact on display at a museum or a heritage site. The driving factor of this framework was the fact that the presence of security cameras has become universal, including at sites of cultural heritage. ARTYCUL used the video streams of closed-circuit televisions (CCTV) cameras installed in such premises to detect human figures, and their coordinates with respect to the camera frames were used to visualize the density of visitors around the specific display items. Such a framework that can display the popularity of artifacts would aid the curators towards a more optimal organization. Moreover, it could also help to gauge if a certain display item were neglected due to incorrect placement. While items of similar interest can be placed in vicinity of each other, an online recommendation system may also use the reputation of an artifact to catch the eye of the visitors. Artificial intelligence-based solutions are well suited for analysis of internet of things (IoT) traffic due to the inherent veracity and volatile nature of the transmissions. The work done for the development of ARTYCUL provided a deeper insight into the avenues for applications of IoT technology to the cultural heritage domain, and suitability of ML to process real-time data at a fast pace. While we also observed common issues that hinder the utilization of IoT in the cultural domain, the proposed framework was designed keeping in mind the same obstacles and a preference for backward compatibility.

Matched MeSH terms: Artifacts
Accurate wavelet thresholding method for ECG signals

Yu K, Feng L, Chen Y, Wu M, Zhang Y, Zhu P, et al.

Comput Biol Med, 2024 Feb;169:107835.
PMID: 38096762 DOI: 10.1016/j.compbiomed.2023.107835

Current wavelet thresholding methods for cardiogram signals captured by flexible wearable sensors face a challenge in achieving both accurate thresholding and real-time signal denoising. This paper proposes a real-time accurate thresholding method based on signal estimation, specifically the normalized ACF, as an alternative to traditional noise estimation without the need for parameter fine-tuning and extensive data training. This method is experimentally validated using a variety of electrocardiogram (ECG) signals from different databases, each containing specific types of noise such as additive white Gaussian (AWG) noise, baseline wander noise, electrode motion noise, and muscle artifact noise. Although this method only slightly outperforms other methods in removing AWG noise in ECG signals, it far outperforms conventional methods in removing other real noise. This is attributed to the method's ability to accurately distinguish not only AWG noise that is significantly different spectrum of the ECG signal, but also real noise with similar spectra. In contrast, the conventional methods are effective only for AWG noise. In additional, this method improves the denoising visualization of the measured ECG signals and can be used to optimize other parameters of other wavelet methods to enhancing the denoised periodic signals, thereby improving diagnostic accuracy.

Matched MeSH terms: Artifacts
Adaptive template matching of photoplethysmogram pulses to detect motion artefact

Lim PK, Ng SC, Lovell NH, Yu YP, Tan MP, McCombie D, et al.

Physiol Meas, 2018 10 11;39(10):105005.
PMID: 30183675 DOI: 10.1088/1361-6579/aadf1e

OBJECTIVE: The photoplethysmography (PPG) signal, commonly used in the healthcare settings, is easily affected by movement artefact leading to errors in the extracted heart rate and SpO2 estimates. This study aims to develop an online artefact detection system based on adaptive (dynamic) template matching, suitable for continuous PPG monitoring during daily living activities or in the intensive care units (ICUs).
APPROACH: Several master templates are initially generated by applying principal component analysis to data obtained from the PhysioNet MIMIC II database. The master template is then updated with each incoming clean PPG pulse. The correlation coefficient is used to classify the PPG pulse into either good or bad quality categories. The performance of our algorithm was evaluated using data obtained from two different sources: (i) our own data collected from 19 healthy subjects using the wearable Sotera Visi Mobile system (Sotera Wireless Inc.) as they performed various movement types; and (ii) ICU data provided by the PhysioNet MIMIC II database. The developed algorithm was evaluated against a manually annotated 'gold standard' (GS).
MAIN RESULTS: Our algorithm achieved an overall accuracy of 91.5% ± 2.9%, with a sensitivity of 94.1% ± 2.7% and a specificity of 89.7% ± 5.1%, when tested on our own data. When applying the algorithm to data from the PhysioNet MIMIC II database, it achieved an accuracy of 98.0%, with a sensitivity and specificity of 99.0% and 96.1%, respectively.
SIGNIFICANCE: The proposed method is simple and robust against individual variations in the PPG characteristics, thus making it suitable for a diverse range of datasets. Integration of the proposed artefact detection technique into remote monitoring devices could enhance reliability of the PPG-derived physiological parameters.

Matched MeSH terms: Artifacts
Fulltext Advancements of data anomaly detection research in wireless sensor networks: a survey and open issues

Rassam MA, Zainal A, Maarof MA

Sensors (Basel), 2013;13(8):10087-122.
PMID: 23966182 DOI: 10.3390/s130810087

Wireless Sensor Networks (WSNs) are important and necessary platforms for the future as the concept "Internet of Things" has emerged lately. They are used for monitoring, tracking, or controlling of many applications in industry, health care, habitat, and military. However, the quality of data collected by sensor nodes is affected by anomalies that occur due to various reasons, such as node failures, reading errors, unusual events, and malicious attacks. Therefore, anomaly detection is a necessary process to ensure the quality of sensor data before it is utilized for making decisions. In this review, we present the challenges of anomaly detection in WSNs and state the requirements to design efficient and effective anomaly detection models. We then review the latest advancements of data anomaly detection research in WSNs and classify current detection approaches in five main classes based on the detection methods used to design these approaches. Varieties of the state-of-the-art models for each class are covered and their limitations are highlighted to provide ideas for potential future works. Furthermore, the reviewed approaches are compared and evaluated based on how well they meet the stated requirements. Finally, the general limitations of current approaches are mentioned and further research opportunities are suggested and discussed.

Matched MeSH terms: Artifacts*
Algorithms that eliminate the effects of calibration artefact and trial-imposed offsets of Masimo oximeter in BOOST-NZ trial

Zahari M, Lee DS, Darlow BA

J Clin Monit Comput, 2016 Oct;30(5):669-78.
PMID: 26282827 DOI: 10.1007/s10877-015-9752-1

The displayed readings of Masimo pulse oximeters used in the Benefits Of Oxygen Saturation Targeting (BOOST) II and related trials in very preterm babies were influenced by trial-imposed offsets and an artefact in the calibration software. A study was undertaken to implement new algorithms that eliminate the effects of offsets and artefact. In the BOOST-New Zealand trial, oxygen saturations were averaged and stored every 10 s up to 36 weeks' post-menstrual age. Two-hundred and fifty-seven of 340 babies enrolled in the trial had at least two weeks of stored data. Oxygen saturation distribution patterns corresponding with a +3 % or -3 % offset in the 85-95 % range were identified together with that due to the calibration artefact. Algorithms involving linear and quadratic interpolations were developed, implemented on each baby of the dataset and validated using the data of a UK preterm baby, as recorded from Masimo oximeters with the original software and a non-offset Siemens oximeter. Saturation distributions obtained were compared for both groups. There were a flat region at saturations 85-87 % and a peak at 96 % from the lower saturation target oximeters, and at 93-95 and 84 % respectively from the higher saturation target oximeters. The algorithms lowered the peaks and redistributed the accumulated frequencies to the flat regions and artefact at 87-90 %. The resulting distributions were very close to those obtained from the Siemens oximeter. The artefact and offsets of the Masimo oximeter's software had been addressed to determine the true saturation readings through the use of novel algorithms. The implementation would enable New Zealand data be included in the meta-analysis of BOOST II trials, and be used in neonatal oxygen studies.

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
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
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 An efficient post-processing adaptive filtering technique to rectifying the flickering effects

Gandam A, Sidhu JS, Verma S, Jhanjhi NZ, Nayyar A, Abouhawwash M, et al.

PLoS One, 2021;16(5):e0250959.
PMID: 33970949 DOI: 10.1371/journal.pone.0250959

Compression at a very low bit rate(≤0.5bpp) causes degradation in video frames with standard decoding algorithms like H.261, H.262, H.264, and MPEG-1 and MPEG-4, which itself produces lots of artifacts. This paper focuses on an efficient pre-and post-processing technique (PP-AFT) to address and rectify the problems of quantization error, ringing, blocking artifact, and flickering effect, which significantly degrade the visual quality of video frames. The PP-AFT method differentiates the blocked images or frames using activity function into different regions and developed adaptive filters as per the classified region. The designed process also introduces an adaptive flicker extraction and removal method and a 2-D filter to remove ringing effects in edge regions. The PP-AFT technique is implemented on various videos, and results are compared with different existing techniques using performance metrics like PSNR-B, MSSIM, and GBIM. Simulation results show significant improvement in the subjective quality of different video frames. The proposed method outperforms state-of-the-art de-blocking methods in terms of PSNR-B with average value lying between (0.7-1.9db) while (35.83-47.7%) reduced average GBIM keeping MSSIM values very close to the original sequence statistically 0.978.

Matched MeSH terms: Artifacts
An evolution of image source camera attribution approaches

Jahanirad M, Wahab AW, Anuar NB

Forensic Sci Int, 2016 May;262:242-75.
PMID: 27060542 DOI: 10.1016/j.forsciint.2016.03.035

Camera attribution plays an important role in digital image forensics by providing the evidence and distinguishing characteristics of the origin of the digital image. It allows the forensic analyser to find the possible source camera which captured the image under investigation. However, in real-world applications, these approaches have faced many challenges due to the large set of multimedia data publicly available through photo sharing and social network sites, captured with uncontrolled conditions and undergone variety of hardware and software post-processing operations. Moreover, the legal system only accepts the forensic analysis of the digital image evidence if the applied camera attribution techniques are unbiased, reliable, nondestructive and widely accepted by the experts in the field. The aim of this paper is to investigate the evolutionary trend of image source camera attribution approaches from fundamental to practice, in particular, with the application of image processing and data mining techniques. Extracting implicit knowledge from images using intrinsic image artifacts for source camera attribution requires a structured image mining process. In this paper, we attempt to provide an introductory tutorial on the image processing pipeline, to determine the general classification of the features corresponding to different components for source camera attribution. The article also reviews techniques of the source camera attribution more comprehensively in the domain of the image forensics in conjunction with the presentation of classifying ongoing developments within the specified area. The classification of the existing source camera attribution approaches is presented based on the specific parameters, such as colour image processing pipeline, hardware- and software-related artifacts and the methods to extract such artifacts. The more recent source camera attribution approaches, which have not yet gained sufficient attention among image forensics researchers, are also critically analysed and further categorised into four different classes, namely, optical aberrations based, sensor camera fingerprints based, processing statistics based and processing regularities based, to present a classification. Furthermore, this paper aims to investigate the challenging problems, and the proposed strategies of such schemes based on the suggested taxonomy to plot an evolution of the source camera attribution approaches with respect to the subjective optimisation criteria over the last decade. The optimisation criteria were determined based on the strategies proposed to increase the detection accuracy, robustness and computational efficiency of source camera brand, model or device attribution.

Matched MeSH terms: Artifacts
Fulltext An intense F-FDG pulmonary microfocus on PET without detectable abnormality on CT: A manifestation of an iatrogenic FDG pulmonary embolus

Fathinul Fikri A, Lau W

Biomed Imaging Interv J, 2010 10 01;6(4):e37.
PMID: 21611073 DOI: 10.2349/biij.6.4.e37

An incidental finding of an intense focus of (18)F-Fluorodeoxyglucose (FDG) pulmonary uptake on positron emission tomography (PET) without detectable lesions on computed tomography (CT) is highly suggestive of FDG microembolus. Its microscopic nature means it is undetectable on CT. It is an artefact attributable to (18)F-FDG-tracer contamination at the injection site. This paper reports a case of a 61 year-old lady with a past history of breast carcinoma, in whom follow-up PET/CT images demonstrated an incidental intense FDG pulmonary abnormality. A follow-up PET/CT seven months later demonstrated complete resolution of the abnormality.

Matched MeSH terms: Artifacts

Filters

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links