Displaying publications 1 - 20 of 103 in total

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  1. Dorsal Hand Vein Image Enhancement Using Fusion of CLAHE and Fuzzy Adaptive Gamma
    Yakno M, Mohamad-Saleh J, Ibrahim MZ
    Sensors (Basel), 2021 Sep 27;21(19).
    PMID: 34640769 DOI: 10.3390/s21196445
    Enhancement of captured hand vein images is essential for a number of purposes, such as accurate biometric identification and ease of medical intravenous access. This paper presents an improved hand vein image enhancement technique based on weighted average fusion of contrast limited adaptive histogram equalization (CLAHE) and fuzzy adaptive gamma (FAG). The proposed technique is applied using three stages. Firstly, grey level intensities with CLAHE are locally applied to image pixels for contrast enhancement. Secondly, the grey level intensities are then globally transformed into membership planes and modified with FAG operator for the same purposes. Finally, the resultant images from CLAHE and FAG are fused using improved weighted averaging methods for clearer vein patterns. Then, matched filter with first-order derivative Gaussian (MF-FODG) is employed to segment vein patterns. The proposed technique was tested on self-acquired dorsal hand vein images as well as images from the SUAS databases. The performance of the proposed technique is compared with various other image enhancement techniques based on mean square error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity index measurement (SSIM). The proposed enhancement technique's impact on the segmentation process has also been evaluated using sensitivity, accuracy, and dice coefficient. The experimental results show that the proposed enhancement technique can significantly enhance the hand vein patterns and improve the detection of dorsal hand veins.
    Matched MeSH terms: Image Enhancement*
  2. Fulltext Perbandingan dos glandular purata payudara berdasarkan kombinasi anod/penuras tungsten/rhodium dan tungsten/argentum pada mamografi digital
    Chelliah, Kanaga Kumari, Lumin, Felecia
    Jurnal Sains Kesihatan Malaysia, 2012;10(1):53-56.
    MyJurnal
    Mamografi adalah cara paling efektif untuk mengesan keabnormalan payudara di kalangan wanita. Namun, mamografi dipercayai boleh menyebabkan karsinogenesis aruhan sinaran. Justeru pengukuran dos adalah penting untuk menganggar risiko dan mengawal kualiti imej. Kajian ini dijalankan untuk membandingkan dos glandular purata (AGD) yang diperolehi fantom payudara berdasarkan dua kombinasi anod/penuras yang berbeza iaitu tungsten/rhodium (W/Rh) dan tungsten/argentum (W/Ag). Fantom payudara CIRS 012A didedahkan pada projeksi kraniokaudal (CC) menggunakan sistem mamografi digital Hologic Selenia. Kerma udara kemasukan permukaan (ESAK) diukur menggunakan dosimeter pendar cahaya terma (TLD). AGD diperolehi daripada pengiraan asas ESAK dengan faktor penukaran berdasarkan formula Euref. Ujian t tak bersandar menunjukkan perbezaan bererti dalam purata AGD yang diperolehi. Purata AGD W/Rh adalah lebih tinggi berbanding purata AGD W/Ag (p = 0.002, 95% CI: 0.22, 0.53). Kesimpulannya, penggunaan W/Ag menyumbang kepada pengurangan dos semasa pemeriksaan mamografi.
    Matched MeSH terms: Radiographic Image Enhancement
  3. Fulltext Optimization of exposure parameters in full field digital mammography using figure of merit. [Pengoptimuman parameter dedahan dalam mamografi digital medan penuh menggunakan rajah merit]
    Laila Suryani Elias, Eng M, Ang W, Chelliah K, Abd Aziz Tajuddin, Arasaratnam S, et al.
    Sains Malaysiana, 2010;39:299-303.
    Mammography is used as a screening tool for early detection of breast cancer. However, the radiation dose used should be as low as possible to minimize any effects on asymptomatic woman while maintaining the diagnostic value of the image as mammography is done annually. This study was done to determine the optimum exposure parameter in exposure control mode (AEC) for two combinations of anode/filter which were molybdenum/molybdenum (Mo/Mo) and molybdenum/rhodium (Mo/Rh) using the Lorad Selenia digital mammography system at the Women’s Breast Clinic, National Cancer Society (NCS). A CIRS012A mammography research of phantom 4 cm thickness with 50% glandularity was exposed in the cranio-caudal projection. TLD 100H was used to measure the entrance surface air kerma (ESAK). The AGD values were then calculated from the ESAK values, incorporating three correction factors (g, c and s) according to Euref protocol. Image quality was evaluated using signal to noise ratio (SNR). Figure of Merit (FOM) which is the ratio of the square of SNR to the AGD shows that 30 kVp is the optimum exposure parameter for a 4 cm thickness phantom with the use of Mo/Rh and Mo/Mo anode/filter combination. Non-parametric Spearman correlation test showed a negative linear relationship between AGD and SNR with increasing tube voltage for both anode/filters.
    Keywords: Average glandular dose; CIRS012A phantom; exposure; full field digital mammography
    Study site: Women’s Breast Clinic, National Cancer Society (NCS), Kuala Lumpur, Malaysia
    Matched MeSH terms: Radiographic Image Enhancement
  4. Fulltext Local convexity-preserving C2 rational cubic spline for convex data
    Abbas M, Abd Majid A, Ali JM
    ScientificWorldJournal, 2014;2014:391568.
    PMID: 24757421 DOI: 10.1155/2014/391568
    We present the smooth and visually pleasant display of 2D data when it is convex, which is contribution towards the improvements over existing methods. This improvement can be used to get the more accurate results. An attempt has been made in order to develop the local convexity-preserving interpolant for convex data using C(2) rational cubic spline. It involves three families of shape parameters in its representation. Data dependent sufficient constraints are imposed on single shape parameter to conserve the inherited shape feature of data. Remaining two of these shape parameters are used for the modification of convex curve to get a visually pleasing curve according to industrial demand. The scheme is tested through several numerical examples, showing that the scheme is local, computationally economical, and visually pleasing.
    Matched MeSH terms: Image Enhancement/methods
  5. A comparative study of computed radiography-based mammography using digital phosphor storage plate and full field digital mammography
    Chelliah KK, Tamanang S, Bt Elias LS, Ying KY
    Indian J Med Sci, 2013 11 2;67(1-2):23-8.
    PMID: 24178338
    BACKGROUND: Two digital mammography systems, based on different physical concepts, have been introduced in the last few years namely the full-field digital mammography (FFDM) system and computed radiography-based mammography using digital storage phosphor plate (DSPM).

    AIMS: The objective of this study was to compare the image quality for DSPM and FFDM using a grading scale based on previously published articles.

    MATERIALS AND METHODS: This comparative diagnostic study was done for 5-month duration at the Breast Clinic. The system used was the Lorad Selenia FFDM system and the Mammomat 3000 Nova DSPM system. The craniocaudal and mediolateral oblique projections were done on both breast on 58 asymptomatic women using both DSPM and FFDM. The mammograms were evaluated for eight criteria of image quality: Tissue coverage, compression, exposure, contrast, resolution, noise, artifact, and sharpness by two independent radiologists.

    STATISTICAL ANALYSIS: Wilcoxon Signed Rank Test and Weighted Kappa.

    RESULTS: FFDM was rated significantly better (P < 0.05) for five aspects: Tissue coverage, compression, contrast, exposure, and resolution and equal to DSPM for sharpness, noise, and artifact.

    CONCLUSION: FFDM was superior in five aspects and equal to DSPM for three aspects of image quality.

    Matched MeSH terms: Radiographic Image Enhancement/instrumentation; Radiographic Image Enhancement/methods*
  6. Fulltext A critical comparison of three full field digital mammography systems using figure of merit
    Kanaga KC, Yap HH, Laila SE, Sulaiman T, Zaharah M, Shantini AA
    Med J Malaysia, 2010 Jun;65(2):119-22.
    PMID: 23756795 MyJurnal
    Full field digital mammography (FFDM) has been progressively introduced in medical centers in recent years. However, it is questionable which exposure parameters are suitable in order to reduce the glandular breast doses as they are related to induced carcinogenesis. The goal of this study was to compare the average glandular doses (AGD) and image quality of three FFDM systems namely Siemens Mammomat NovationDR, Hologic Lorad Selenia and General Electric Senographe Essential using a Figure of Merit. A Computerized Imaging Reference Systems (CIRS) tissue equivalent breast phantom which consists of phototimer compensation plate with different thickness and glandularity was exposed in fully automatic exposure control mode in the cranio-caudal projection similar to clinical settings. Thermoluminescent dosimeter 100H (TLD- 100H) was used to measure the entrance surface air kerma (ESAK), the AGD was calculated using European protocol whilst the image quality was assessed quantitatively by measuring the contrast to noise ratio (CNR) value. The obtained values were used to calculate the Figure of Merit (FOM) to analyze the effectiveness of the system. Repeated Measures ANOVA analysis showed that there is a significant difference (p<0.05) in the mean value of AGD and CNR between the three FFDM systems. Hologic Lorad Selenia system contrbuted the highest AGD value while General Electric Senographe Essential had the highest CNR and FOM value. In conclusion, this study may provide an objective criterion during the selection of a mammography unit by using the figure of merit for screening or diagnostic purpose.
    Matched MeSH terms: Radiographic Image Enhancement*
  7. 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: Image Enhancement/methods
  8. Comparison study of the MRI shoulder PROPELLER technique with differential image quality by variation of shoulder coils
    Khairi M, Zakaria F, Supar R, Mohd Z
    Med J Malaysia, 2024 Mar;79(Suppl 1):74-81.
    PMID: 38555889
    INTRODUCTION: Motion and pulsation artifacts are the most prominent types of artifacts in Magnetic Resonance Imaging (MRI) of the shoulder. Therefore, this study examined the Periodically Rotating Overlapping Parallel Lines with Enhanced Reconstruction (PROPELLER) technique with small flex coil (SFC) and dedicated shoulder coil (DSC) for the reduction of motion and pulsation artifacts. The signalto- noise ratio (SNR) and contrast-to-noise ratio (CNR) of the standard proton density fat saturation (PDFS) pulse sequence and the PROPELLER proton density fat saturation (PROPELLER PDFS) pulse sequence were also evaluated.

    MATERIALS AND METHODS: Eighteen (18) participants who met the inclusion and exclusion criteria were scanned using a standard non-contrast MRI shoulder protocol including the PDFS pulse sequence and the PROPELLER PDFS pulse sequence using a small flex coil and a dedicated shoulder coil. Two experienced musculoskeletal (MSK) radiologists evaluated and graded the presence of artifacts on the MR images and the SNR and CNR were measured quantitatively.

    RESULTS: The non-parametric Wilcoxon Signed Rank test revealed a significant reduction in motion and pulsation artifacts between the PROPELLER PDFS pulse sequence and the standard PDFS pulse sequence. In addition, the nonparametric Mann-Whitney U test revealed that the mean rank of SNR for the standard sequence was statistically significant when compared to the PROPELLER sequence for both coil types. The CNR of the PROPELLER sequence was statistically significant between fat-fluid, bone-fluid, bonetendon, bone-muscle, and muscle-fluid when using SFC and DSC.

    CONCLUSION: This study proved that the PROPELLER-PDFS pulse sequence effectively eliminates motion and pulsation artifacts, regardless of the coils utilised. The PROPELLERPDFS pulse sequence can therefore be implemented into the standard MRI shoulder procedure.

    Matched MeSH terms: Image Enhancement/methods
  9. Improvement of digital mammogram images using histogram equalization, histogram stretching and median filter
    Langarizadeh M, Mahmud R, Ramli AR, Napis S, Beikzadeh MR, Rahman WE
    J Med Eng Technol, 2011 Feb;35(2):103-8.
    PMID: 21204610 DOI: 10.3109/03091902.2010.542271
    Breast cancer is one of the most important diseases in females worldwide. According to the Malaysian Oncological Society, about 4% of women who are 40 years old and above are involved have breast cancer. Masses and microcalcifications are two important signs of breast cancer diagnosis on mammography. Enhancement techniques, i.e. histogram equalization, histogram stretching and median filters, were used to provide better visualization for radiologists in order to help early detection of breast abnormalities. In this research 60 digital mammogram images which includes 20 normal and 40 confirmed diagnosed cancerous cases were selected and manipulated using the mentioned techniques. The original and manipulated images were scored by three expert radiologists. Results showed that the selected methods have a positive significant effect on image quality.
    Matched MeSH terms: Radiographic Image Enhancement
  10. Fulltext A New Local Fractional Entropy-Based Model for Kidney MRI Image Enhancement
    Al-Shamasneh AR, Jalab HA, Palaiahnakote S, Obaidellah UH, Ibrahim RW, El-Melegy MT
    Entropy (Basel), 2018 May 05;20(5).
    PMID: 33265434 DOI: 10.3390/e20050344
    Kidney image enhancement is challenging due to the unpredictable quality of MRI images, as well as the nature of kidney diseases. The focus of this work is on kidney images enhancement by proposing a new Local Fractional Entropy (LFE)-based model. The proposed model estimates the probability of pixels that represent edges based on the entropy of the neighboring pixels, which results in local fractional entropy. When there is a small change in the intensity values (indicating the presence of edge in the image), the local fractional entropy gives fine image details. Similarly, when no change in intensity values is present (indicating smooth texture), the LFE does not provide fine details, based on the fact that there is no edge information. Tests were conducted on a large dataset of different, poor-quality kidney images to show that the proposed model is useful and effective. A comparative study with the classical methods, coupled with the latest enhancement methods, shows that the proposed model outperforms the existing methods.
    Matched MeSH terms: Image Enhancement
  11. Fulltext Radiographic imaging of steel oval lock carabiner by using computed radiography: a pilot study
    Nadzirah Mohamad Radzi, Zafri Azran Abdul Majid
    International Journal of Allied Health Sciences, 2018;2(2):310-318.
    MyJurnal
    Carabiner is one of Personal Protective Equipment (PPE), which is used to protect the users from hazards by reducing any chance of serious injury. Thus, it is very important to detect even a small
    defect on the component before it becomes worse that could give harm to the users. The aim of this paper is to find out the appropriate imaging technical factors of steel carabiner by using computed radiography (CR). Methods: Radiographic images of carabiner were obtained by manipulating the values of kVp and mAs with respect to contrast and density. A preliminary study was carried out to determine the exposure factor combination in order to produce perceptible visual quality of radiographic images. Positioning techniques applied in this study were whole view (open-gate and close-gate position) and screw view (open-gate and close-gate position). An assessor was invited to evaluate the radiographs by using Image Quality Criteria Scoring (ICS) adapted from European Guidelines on Quality Criteria for Diagnostic Radiographic Images. Results: Findings showed that the optimum values of kVp and mAs in imaging whole view (open-gate and close-gate) carabiner were 133 kVp and 28 mAs while, for screw view (opengate and close-gate) the range of kVp and mAs preferred were 121 kVp to 133 kVp and 28 mAs to 36 mAs respectively. Conclusion: This study has found that the use of medical CR to expose metal steel such as
    carabiner is accepted. By manipulating the imaging parameters, CR can produce a good quality image of carabiner.
    Matched MeSH terms: Radiographic Image Enhancement
  12. Autonomous Vision-Based Primary Distribution Systems Porcelain Insulators Inspection Using UAVs
    Rahman EU, Zhang Y, Ahmad S, Ahmad HI, Jobaer S
    Sensors (Basel), 2021 Feb 02;21(3).
    PMID: 33540500 DOI: 10.3390/s21030974
    The early detection of damaged (partially broken) outdoor insulators in primary distribution systems is of paramount importance for continuous electricity supply and public safety. Unmanned aerial vehicles (UAVs) present a safer, autonomous, and efficient way to examine the power system components without closing the power distribution system. In this work, a novel dataset is designed by capturing real images using UAVs and manually generated images collected to overcome the data insufficiency problem. A deep Laplacian pyramid-based super-resolution network is implemented to reconstruct high-resolution training images. To improve the visibility of low-light images, a low-light image enhancement technique is used for the robust exposure correction of the training images. A different fine-tuning strategy is implemented for fine-tuning the object detection model to increase detection accuracy for the specific faulty insulators. Several flight path strategies are proposed to overcome the shuttering effect of insulators, along with providing a less complex and time- and energy-efficient approach for capturing a video stream of the power system components. The performance of different object detection models is presented for selecting the most suitable one for fine-tuning on the specific faulty insulator dataset. For the detection of damaged insulators, our proposed method achieved an F1-score of 0.81 and 0.77 on two different datasets and presents a simple and more efficient flight strategy. Our approach is based on real aerial inspection of in-service porcelain insulators by extensive evaluation of several video sequences showing robust fault recognition and diagnostic capabilities. Our approach is demonstrated on data acquired by a drone in Swat, Pakistan.
    Matched MeSH terms: Image Enhancement
  13. Digital radiographic image enhancement for weld defect detection using smoothing and morphological transformations
    Suhaila Abdul Halim, Arsmah Ibrahim, Yupiter Harangan Prasada Manurung
    Scientific Research Journal, 2012;9(1):15-27.
    MyJurnal
    Accurate inspection of welded materials is important in relation to achieve acceptable standards. Radiography, a non-destructive test method, is commonly used to evaluate the internal condition of a material with respect to defect detection. The presence of noise in low resolution of radiographic images significantly complicates analysis; therefore attaining higher quality radiographic images makes defect detection more readily achievable. This paper presents a study pertaining to the quality enhancement of radiographic images with respect to different types of defects. A series of digital radiographic weld flaw images were smoothed using multiple smoothing techniques to remove inherent noise followed by top and bottom hat morphological transformations. Image quality was evaluated quantitatively with respect to SNR, PSNR and MAE. The results indicate that smoothing enhances the quality of radiographic images, thereby promoting defect detection with the respect to original radiographic images.
    Matched MeSH terms: Radiographic Image Enhancement
  14. Improvement to the scanning electron microscope image adaptive Canny optimization colorization by pseudo-mapping
    Lo TY, Sim KS, Tso CP, Nia ME
    Scanning, 2014 Sep-Oct;36(5):530-9.
    PMID: 25139061 DOI: 10.1002/sca.21152
    An improvement to the previously proposed adaptive Canny optimization technique for scanning electron microscope image colorization is reported. The additional feature, called pseudo-mapping technique, is that the grayscale markings are temporarily mapped to a set of pre-defined pseudo-color map as a mean to instill color information for grayscale colors in chrominance channels. This allows the presence of grayscale markings to be identified; hence optimization colorization of grayscale colors is made possible. This additional feature enhances the flexibility of scanning electron microscope image colorization by providing wider range of possible color enhancement. Furthermore, the nature of this technique also allows users to adjust the luminance intensities of selected region from the original image within certain extent.
    Matched MeSH terms: Image Enhancement
  15. A contrast stretching bilateral closing top-hat Otsu threshold technique for crack detection in images
    Sim KS, Kho YY, Tso CP, Nia ME, Ting HY
    Scanning, 2013 Mar-Apr;35(2):75-87.
    PMID: 22777599 DOI: 10.1002/sca.21037
    Detection of cracks from stainless steel pipe images is done using contrast stretching technique. The technique is based on an image filter technique through mathematical morphology that can expose the cracks. The cracks are highlighted and noise removal is done efficiently while still retaining the edges. An automated crack detection system with a camera platform has been successfully implemented. We compare crack extraction in terms of quality measures with those of Otsu's threshold technique and the another technique (Iyer and Sinha, 2005). The algorithm shown is able to achieve good results and perform better than these other techniques.
    Matched MeSH terms: Image Enhancement
  16. Fulltext Exploring the effect of image enhancement techniques on COVID-19 detection using chest X-ray images
    Rahman T, Khandakar A, Qiblawey Y, Tahir A, Kiranyaz S, Abul Kashem SB, et al.
    Comput Biol Med, 2021 May;132:104319.
    PMID: 33799220 DOI: 10.1016/j.compbiomed.2021.104319
    Computer-aided diagnosis for the reliable and fast detection of coronavirus disease (COVID-19) has become a necessity to prevent the spread of the virus during the pandemic to ease the burden on the healthcare system. Chest X-ray (CXR) imaging has several advantages over other imaging and detection techniques. Numerous works have been reported on COVID-19 detection from a smaller set of original X-ray images. However, the effect of image enhancement and lung segmentation of a large dataset in COVID-19 detection was not reported in the literature. We have compiled a large X-ray dataset (COVQU) consisting of 18,479 CXR images with 8851 normal, 6012 non-COVID lung infections, and 3616 COVID-19 CXR images and their corresponding ground truth lung masks. To the best of our knowledge, this is the largest public COVID positive database and the lung masks. Five different image enhancement techniques: histogram equalization (HE), contrast limited adaptive histogram equalization (CLAHE), image complement, gamma correction, and balance contrast enhancement technique (BCET) were used to investigate the effect of image enhancement techniques on COVID-19 detection. A novel U-Net model was proposed and compared with the standard U-Net model for lung segmentation. Six different pre-trained Convolutional Neural Networks (CNNs) (ResNet18, ResNet50, ResNet101, InceptionV3, DenseNet201, and ChexNet) and a shallow CNN model were investigated on the plain and segmented lung CXR images. The novel U-Net model showed an accuracy, Intersection over Union (IoU), and Dice coefficient of 98.63%, 94.3%, and 96.94%, respectively for lung segmentation. The gamma correction-based enhancement technique outperforms other techniques in detecting COVID-19 from the plain and the segmented lung CXR images. Classification performance from plain CXR images is slightly better than the segmented lung CXR images; however, the reliability of network performance is significantly improved for the segmented lung images, which was observed using the visualization technique. The accuracy, precision, sensitivity, F1-score, and specificity were 95.11%, 94.55%, 94.56%, 94.53%, and 95.59% respectively for the segmented lung images. The proposed approach with very reliable and comparable performance will boost the fast and robust COVID-19 detection using chest X-ray images.
    Matched MeSH terms: Image Enhancement
  17. Fulltext Subspace-based technique for speckle noise reduction in ultrasound images
    Yahya N, Kamel NS, Malik AS
    Biomed Eng Online, 2014;13(1):154.
    PMID: 25421914 DOI: 10.1186/1475-925X-13-154
    Ultrasound imaging is a very essential technique in medical diagnosis due to its being safe, economical and non-invasive nature. Despite its popularity, the US images, however, are corrupted with speckle noise, which reduces US images qualities, hampering image interpretation and processing stage. Hence, there are many efforts made by researches to formulate various despeckling methods for speckle reduction in US images.
    Matched MeSH terms: Image Enhancement/methods*
  18. Fulltext A new human heart vessel identification, segmentation and 3D reconstruction mechanism
    Al-Surmi A, Wirza R, Mahmod R, Khalid F, Dimon MZ
    J Cardiothorac Surg, 2014;9:161.
    PMID: 25274253 DOI: 10.1186/s13019-014-0161-1
    The identification and segmentation of inhomogeneous image regions is one of the most challenging issues nowadays. The surface vessels of the human heart are important for the surgeons to locate the region where to perform the surgery and to avoid surgical injuries. In addition, such identification, segmentation, and visualisation helps novice surgeons in the training phase of cardiac surgery.
    Matched MeSH terms: Image Enhancement*
  19. Fulltext MATIN: a random network coding based framework for high quality peer-to-peer live video streaming
    Barekatain B, Khezrimotlagh D, Aizaini Maarof M, Ghaeini HR, Salleh S, Quintana AA, et al.
    PLoS One, 2013;8(8):e69844.
    PMID: 23940530 DOI: 10.1371/journal.pone.0069844
    In recent years, Random Network Coding (RNC) has emerged as a promising solution for efficient Peer-to-Peer (P2P) video multicasting over the Internet. This probably refers to this fact that RNC noticeably increases the error resiliency and throughput of the network. However, high transmission overhead arising from sending large coefficients vector as header has been the most important challenge of the RNC. Moreover, due to employing the Gauss-Jordan elimination method, considerable computational complexity can be imposed on peers in decoding the encoded blocks and checking linear dependency among the coefficients vectors. In order to address these challenges, this study introduces MATIN which is a random network coding based framework for efficient P2P video streaming. The MATIN includes a novel coefficients matrix generation method so that there is no linear dependency in the generated coefficients matrix. Using the proposed framework, each peer encapsulates one instead of n coefficients entries into the generated encoded packet which results in very low transmission overhead. It is also possible to obtain the inverted coefficients matrix using a bit number of simple arithmetic operations. In this regard, peers sustain very low computational complexities. As a result, the MATIN permits random network coding to be more efficient in P2P video streaming systems. The results obtained from simulation using OMNET++ show that it substantially outperforms the RNC which uses the Gauss-Jordan elimination method by providing better video quality on peers in terms of the four important performance metrics including video distortion, dependency distortion, End-to-End delay and Initial Startup delay.
    Matched MeSH terms: Image Enhancement*
  20. A comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram
    Meselhy Eltoukhy M, Faye I, Belhaouari Samir B
    Comput Biol Med, 2010 Apr;40(4):384-91.
    PMID: 20163793 DOI: 10.1016/j.compbiomed.2010.02.002
    This paper presents a comparative study between wavelet and curvelet transform for breast cancer diagnosis in digital mammogram. Using multiresolution analysis, mammogram images are decomposed into different resolution levels, which are sensitive to different frequency bands. A set of the biggest coefficients from each decomposition level is extracted. Then a supervised classifier system based on Euclidian distance is constructed. The performance of the classifier is evaluated using a 2 x 5-fold cross validation followed by a statistical analysis. The experimental results suggest that curvelet transform outperforms wavelet transform and the difference is statistically significant.
    Matched MeSH terms: Image Enhancement/methods*
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