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Publisher: Hindawi   (Total: 298 journals)

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Showing 1 - 200 of 298 Journals sorted alphabetically
Abstract and Applied Analysis     Open Access   (Followers: 3, SJR: 0.512, h-index: 32)
Active and Passive Electronic Components     Open Access   (Followers: 7, SJR: 0.157, h-index: 15)
Advances in Acoustics and Vibration     Open Access   (Followers: 29, SJR: 0.259, h-index: 6)
Advances in Agriculture     Open Access   (Followers: 7)
Advances in Artificial Intelligence     Open Access   (Followers: 16)
Advances in Astronomy     Open Access   (Followers: 37, SJR: 0.351, h-index: 17)
Advances in Bioinformatics     Open Access   (Followers: 18, SJR: 0.421, h-index: 8)
Advances in Chemistry     Open Access   (Followers: 15)
Advances in Civil Engineering     Open Access   (Followers: 34, SJR: 0.338, h-index: 8)
Advances in Condensed Matter Physics     Open Access   (Followers: 8, SJR: 0.248, h-index: 10)
Advances in Decision Sciences     Open Access   (Followers: 5, SJR: 0.231, h-index: 6)
Advances in Electrical Engineering     Open Access   (Followers: 20)
Advances in Fuzzy Systems     Open Access   (Followers: 5, SJR: 0.258, h-index: 7)
Advances in Hematology     Open Access   (Followers: 9, SJR: 0.892, h-index: 18)
Advances in High Energy Physics     Open Access   (Followers: 19, SJR: 0.892, h-index: 19)
Advances in Human-Computer Interaction     Open Access   (Followers: 20, SJR: 0.439, h-index: 9)
Advances in Materials Science and Engineering     Open Access   (Followers: 32, SJR: 0.263, h-index: 11)
Advances in Mathematical Physics     Open Access   (Followers: 5, SJR: 0.332, h-index: 10)
Advances in Medicine     Open Access   (Followers: 2)
Advances in Meteorology     Open Access   (Followers: 18, SJR: 0.498, h-index: 10)
Advances in Multimedia     Open Access   (Followers: 2, SJR: 0.191, h-index: 10)
Advances in Nonlinear Optics     Open Access   (Followers: 5)
Advances in Numerical Analysis     Open Access   (Followers: 4)
Advances in Operations Research     Open Access   (Followers: 11, SJR: 0.343, h-index: 7)
Advances in Optical Technologies     Open Access   (Followers: 3, SJR: 0.283, h-index: 16)
Advances in OptoElectronics     Open Access   (Followers: 5, SJR: 0.973, h-index: 16)
Advances in Orthopedic Surgery     Open Access   (Followers: 10)
Advances in Orthopedics     Open Access   (Followers: 9)
Advances in Pharmacological Sciences     Open Access   (Followers: 6, SJR: 0.695, h-index: 13)
Advances in Physical Chemistry     Open Access   (Followers: 11, SJR: 0.297, h-index: 7)
Advances in Power Electronics     Open Access   (Followers: 26, SJR: 0.26, h-index: 6)
Advances in Preventive Medicine     Open Access   (Followers: 6)
Advances in Public Health     Open Access   (Followers: 23)
Advances in Tribology     Open Access   (Followers: 10, SJR: 0.267, h-index: 6)
Advances in Urology     Open Access   (Followers: 10, SJR: 0.629, h-index: 16)
Advances in Virology     Open Access   (Followers: 7, SJR: 1.04, h-index: 12)
AIDS Research and Treatment     Open Access   (Followers: 3, SJR: 1.125, h-index: 14)
Analytical Cellular Pathology     Open Access   (Followers: 2, SJR: 0.334, h-index: 12)
Anatomy Research Intl.     Open Access   (Followers: 2)
Anemia     Open Access   (Followers: 4, SJR: 0.991, h-index: 11)
Anesthesiology Research and Practice     Open Access   (Followers: 12, SJR: 0.513, h-index: 12)
Applied and Environmental Soil Science     Open Access   (Followers: 17, SJR: 0.53, h-index: 9)
Applied Bionics and Biomechanics     Open Access   (Followers: 8, SJR: 0.23, h-index: 13)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 12)
Archaea     Open Access   (Followers: 3, SJR: 1.248, h-index: 27)
Arthritis     Open Access   (Followers: 4)
Autism Research and Treatment     Open Access   (Followers: 28)
Autoimmune Diseases     Open Access   (Followers: 3, SJR: 0.909, h-index: 17)
Behavioural Neurology     Open Access   (Followers: 7, SJR: 0.696, h-index: 34)
Biochemistry Research Intl.     Open Access   (Followers: 6, SJR: 1.085, h-index: 17)
Bioinorganic Chemistry and Applications     Open Access   (Followers: 9, SJR: 0.286, h-index: 19)
BioMed Research Intl.     Open Access   (Followers: 6, SJR: 0.725, h-index: 59)
Biotechnology Research Intl.     Open Access   (Followers: 2)
Bone Marrow Research     Open Access   (Followers: 2)
Canadian J. of Gastroenterology & Hepatology     Open Access   (Followers: 4, SJR: 0.856, h-index: 53)
Canadian J. of Infectious Diseases and Medical Microbiology     Open Access   (Followers: 4, SJR: 0.409, h-index: 25)
Canadian Respiratory J.     Open Access   (Followers: 1, SJR: 0.503, h-index: 42)
Cardiology Research and Practice     Open Access   (Followers: 8, SJR: 0.941, h-index: 17)
Cardiovascular Psychiatry and Neurology     Open Access   (Followers: 4, SJR: 1.091, h-index: 14)
Case Reports in Anesthesiology     Open Access   (Followers: 10)
Case Reports in Cardiology     Open Access   (Followers: 2)
Case Reports in Critical Care     Open Access   (Followers: 9)
Case Reports in Dentistry     Open Access   (Followers: 4)
Case Reports in Dermatological Medicine     Open Access   (Followers: 2)
Case Reports in Emergency Medicine     Open Access   (Followers: 15)
Case Reports in Endocrinology     Open Access   (SJR: 0.326, h-index: 1)
Case Reports in Gastrointestinal Medicine     Open Access   (Followers: 3)
Case Reports in Genetics     Open Access   (Followers: 1)
Case Reports in Hematology     Open Access   (Followers: 3)
Case Reports in Hepatology     Open Access   (Followers: 1)
Case Reports in Immunology     Open Access   (Followers: 4)
Case Reports in Infectious Diseases     Open Access   (Followers: 5)
Case Reports in Medicine     Open Access   (Followers: 3)
Case Reports in Nephrology     Open Access   (Followers: 4)
Case Reports in Neurological Medicine     Open Access   (Followers: 1)
Case Reports in Obstetrics and Gynecology     Open Access   (Followers: 11)
Case Reports in Oncological Medicine     Open Access   (Followers: 2)
Case Reports in Ophthalmological Medicine     Open Access   (Followers: 3)
Case Reports in Orthopedics     Open Access   (Followers: 7)
Case Reports in Otolaryngology     Open Access   (Followers: 6)
Case Reports in Pathology     Open Access   (Followers: 5)
Case Reports in Pediatrics     Open Access   (Followers: 6)
Case Reports in Psychiatry     Open Access   (Followers: 12)
Case Reports in Pulmonology     Open Access   (Followers: 3)
Case Reports in Radiology     Open Access   (Followers: 9)
Case Reports in Rheumatology     Open Access   (Followers: 4)
Case Reports in Surgery     Open Access   (Followers: 9)
Case Reports in Transplantation     Open Access  
Case Reports in Urology     Open Access   (Followers: 9)
Case Reports in Vascular Medicine     Open Access  
Case Reports in Veterinary Medicine     Open Access   (Followers: 5)
Chemotherapy Research and Practice     Open Access   (Followers: 1)
Child Development Research     Open Access   (Followers: 16)
Chinese J. of Engineering     Open Access   (Followers: 2)
Chinese J. of Mathematics     Open Access  
Cholesterol     Open Access   (Followers: 1, SJR: 0.906, h-index: 12)
Complexity     Hybrid Journal   (Followers: 6, SJR: 0.526, h-index: 27)
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2, SJR: 0.415, h-index: 22)
Computational Intelligence and Neuroscience     Open Access   (Followers: 10, SJR: 0.232, h-index: 30)
Contrast Media & Molecular Imaging     Open Access   (Followers: 3, SJR: 0.932, h-index: 34)
Critical Care Research and Practice     Open Access   (Followers: 10, SJR: 0.916, h-index: 14)
Current Gerontology and Geriatrics Research     Open Access   (Followers: 9, SJR: 0.8, h-index: 12)
Depression Research and Treatment     Open Access   (Followers: 13, SJR: 0.77, h-index: 11)
Dermatology Research and Practice     Open Access   (Followers: 3, SJR: 0.576, h-index: 15)
Diagnostic and Therapeutic Endoscopy     Open Access   (SJR: 0.651, h-index: 18)
Discrete Dynamics in Nature and Society     Open Access   (Followers: 5, SJR: 0.323, h-index: 24)
Disease Markers     Open Access   (Followers: 1, SJR: 0.774, h-index: 49)
Education Research Intl.     Open Access   (Followers: 19)
Emergency Medicine Intl.     Open Access   (Followers: 7)
Enzyme Research     Open Access   (Followers: 4, SJR: 0.457, h-index: 18)
Epilepsy Research and Treatment     Open Access   (Followers: 3)
Evidence-based Complementary and Alternative Medicine     Open Access   (Followers: 18, SJR: 0.615, h-index: 50)
Experimental Diabetes Research     Open Access   (Followers: 11, SJR: 1.591, h-index: 30)
Gastroenterology Research and Practice     Open Access   (Followers: 3, SJR: 0.664, h-index: 21)
Genetics Research Intl.     Open Access   (Followers: 1)
Geofluids     Open Access   (Followers: 4, SJR: 0.693, h-index: 38)
Hepatitis Research and Treatment     Open Access   (Followers: 6)
HPB Surgery     Open Access   (Followers: 5, SJR: 0.798, h-index: 22)
Indian J. of Materials Science     Open Access  
Infectious Diseases in Obstetrics and Gynecology     Open Access   (Followers: 7, SJR: 0.976, h-index: 34)
Influenza Research and Treatment     Open Access   (Followers: 2)
Interdisciplinary Perspectives on Infectious Diseases     Open Access   (Followers: 2, SJR: 0.763, h-index: 15)
Intl. J. of Aerospace Engineering     Open Access   (Followers: 66, SJR: 0.241, h-index: 6)
Intl. J. of Agronomy     Open Access   (Followers: 8, SJR: 0.223, h-index: 2)
Intl. J. of Alzheimer's Disease     Open Access   (Followers: 12, SJR: 1.193, h-index: 25)
Intl. J. of Analysis     Open Access  
Intl. J. of Analytical Chemistry     Open Access   (Followers: 22, SJR: 0.157, h-index: 2)
Intl. J. of Antennas and Propagation     Open Access   (Followers: 11, SJR: 0.385, h-index: 15)
Intl. J. of Bacteriology     Open Access  
Intl. J. of Biodiversity     Open Access   (Followers: 4)
Intl. J. of Biomaterials     Open Access   (Followers: 5, SJR: 0.485, h-index: 10)
Intl. J. of Biomedical Imaging     Open Access   (Followers: 5, SJR: 0.581, h-index: 23)
Intl. J. of Breast Cancer     Open Access   (Followers: 12)
Intl. J. of Cell Biology     Open Access   (Followers: 4, SJR: 2.658, h-index: 25)
Intl. J. of Chemical Engineering     Open Access   (Followers: 7, SJR: 0.361, h-index: 10)
Intl. J. of Chronic Diseases     Open Access   (Followers: 1)
Intl. J. of Computer Games Technology     Open Access   (Followers: 11, SJR: 0.213, h-index: 12)
Intl. J. of Corrosion     Open Access   (Followers: 11, SJR: 0.19, h-index: 7)
Intl. J. of Dentistry     Open Access   (Followers: 6, SJR: 0.558, h-index: 11)
Intl. J. of Differential Equations     Open Access   (Followers: 7, SJR: 0.363, h-index: 11)
Intl. J. of Digital Multimedia Broadcasting     Open Access   (Followers: 5, SJR: 0.144, h-index: 10)
Intl. J. of Electrochemistry     Open Access   (Followers: 8)
Intl. J. of Endocrinology     Open Access   (Followers: 3, SJR: 0.961, h-index: 24)
Intl. J. of Engineering Mathematics     Open Access   (Followers: 3)
Intl. J. of Evolutionary Biology     Open Access   (Followers: 9)
Intl. J. of Family Medicine     Open Access   (Followers: 3)
Intl. J. of Food Science     Open Access   (Followers: 3)
Intl. J. of Forestry Research     Open Access   (Followers: 4)
Intl. J. of Genomics     Open Access   (Followers: 2, SJR: 0.721, h-index: 7)
Intl. J. of Hepatology     Open Access   (Followers: 3)
Intl. J. of Hypertension     Open Access   (Followers: 6, SJR: 0.823, h-index: 20)
Intl. J. of Inflammation     Open Access   (SJR: 0.876, h-index: 14)
Intl. J. of Mathematics and Mathematical Sciences     Open Access   (Followers: 3, SJR: 0.346, h-index: 27)
Intl. J. of Medicinal Chemistry     Open Access   (Followers: 6)
Intl. J. of Microbiology     Open Access   (Followers: 5, SJR: 1.006, h-index: 18)
Intl. J. of Microwave Science and Technology     Open Access   (Followers: 3, SJR: 0.167, h-index: 5)
Intl. J. of Molecular Imaging     Open Access  
Intl. J. of Navigation and Observation     Open Access   (Followers: 20, SJR: 0.411, h-index: 7)
Intl. J. of Nephrology     Open Access   (Followers: 2, SJR: 0.926, h-index: 14)
Intl. J. of Optics     Open Access   (Followers: 7, SJR: 0.262, h-index: 7)
Intl. J. of Otolaryngology     Open Access   (Followers: 3)
Intl. J. of Pediatrics     Open Access   (Followers: 5)
Intl. J. of Peptides     Open Access   (Followers: 4, SJR: 0.73, h-index: 16)
Intl. J. of Photoenergy     Open Access   (Followers: 2, SJR: 0.348, h-index: 28)
Intl. J. of Plant Genomics     Open Access   (Followers: 4, SJR: 1.578, h-index: 20)
Intl. J. of Polymer Science     Open Access   (Followers: 23, SJR: 0.265, h-index: 11)
Intl. J. of Population Research     Open Access   (Followers: 2)
Intl. J. of Proteomics     Open Access   (Followers: 1)
Intl. J. of Reconfigurable Computing     Open Access   (SJR: 0.182, h-index: 8)
Intl. J. of Reproductive Medicine     Open Access   (Followers: 5)
Intl. J. of Rheumatology     Open Access   (Followers: 4, SJR: 1.015, h-index: 18)
Intl. J. of Rotating Machinery     Open Access   (Followers: 2, SJR: 0.402, h-index: 19)
Intl. J. of Spectroscopy     Open Access   (Followers: 8)
Intl. J. of Stochastic Analysis     Open Access   (Followers: 4, SJR: 0.234, h-index: 19)
Intl. J. of Surgical Oncology     Open Access   (Followers: 1, SJR: 0.753, h-index: 11)
Intl. J. of Telemedicine and Applications     Open Access   (Followers: 4, SJR: 0.757, h-index: 14)
Intl. J. of Vascular Medicine     Open Access   (SJR: 0.865, h-index: 16)
Intl. J. of Vehicular Technology     Open Access   (Followers: 4, SJR: 0.169, h-index: 6)
Intl. J. of Zoology     Open Access   (Followers: 1, SJR: 0.389, h-index: 8)
Intl. Scholarly Research Notices     Open Access   (Followers: 207)
ISRN Astronomy and Astrophysics     Open Access   (Followers: 7)
J. of Addiction     Open Access   (Followers: 12)
J. of Advanced Transportation     Hybrid Journal   (Followers: 11, SJR: 0.911, h-index: 24)
J. of Aging Research     Open Access   (Followers: 7, SJR: 1.259, h-index: 23)
J. of Allergy     Open Access   (Followers: 4)
J. of Amino Acids     Open Access   (Followers: 2)
J. of Analytical Methods in Chemistry     Open Access   (Followers: 1, SJR: 0.296, h-index: 13)
J. of Anthropology     Open Access   (Followers: 24)
J. of Applied Chemistry     Open Access   (Followers: 4)
J. of Applied Mathematics     Open Access   (Followers: 2, SJR: 0.341, h-index: 22)
J. of Biomarkers     Open Access  
J. of Biomedical Education     Open Access   (Followers: 2)
J. of Biophysics     Open Access   (Followers: 5, SJR: 0.22, h-index: 5)
J. of Blood Transfusion     Open Access   (Followers: 1)
J. of Botany     Open Access   (Followers: 3, SJR: 0.101, h-index: 2)
J. of Cancer Epidemiology     Open Access   (Followers: 7, SJR: 1.427, h-index: 12)
J. of Chemistry     Open Access   (Followers: 5, SJR: 0.225, h-index: 11)
J. of Combustion     Open Access   (Followers: 17, SJR: 0.27, h-index: 8)
J. of Complex Analysis     Open Access   (Followers: 3)
J. of Computational Engineering     Open Access   (Followers: 1)

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Journal Cover International Journal of Biomedical Imaging
  [SJR: 0.581]   [H-I: 23]   [5 followers]  Follow
    
  This is an Open Access Journal Open Access journal
   ISSN (Print) 1687-4188 - ISSN (Online) 1687-4196
   Published by Hindawi Homepage  [298 journals]
  • Evaluation of Deformable Image Registration for Three-Dimensional Temporal
           Subtraction of Chest Computed Tomography Images

    • Abstract: Purpose. To perform lung image registration for reducing misregistration artifacts on three-dimensional (3D) temporal subtraction of chest computed tomography (CT) images, in order to enhance temporal changes in lung lesions and evaluate these changes after deformable image registration (DIR). Methods. In 10 cases, mutual information (MI) lung mask affine mapping combined with cross-correlation (CC) lung diffeomorphic mapping was used to implement lung volume registration. With advanced normalization tools (ANTs), we used greedy symmetric normalization (greedy SyN) as a transformation model, which involved MI-CC-SyN implementation. The resulting displacement fields were applied to warp the previous (moving) image, which was subsequently subtracted from the current (fixed) image to obtain the lung subtraction image. Results. The average minimum and maximum log-Jacobians were 0.31 and 3.74, respectively. When considering 3D landmark distance, the root-mean-square error changed from an average of 20.82 mm for to to 0.5 mm for to . Clear shadows were observed as enhanced lung nodules and lesions in subtraction images. The lesion shadows showed lesion shrinkage changes over time. Lesion tissue morphology was maintained after DIR. Conclusions. DIR (greedy SyN) effectively and accurately enhanced temporal changes in chest CT images and decreased misregistration artifacts in temporal subtraction images.
      PubDate: Thu, 12 Oct 2017 00:00:00 +000
       
  • Computer-Aided Cobb Measurement Based on Automatic Detection of Vertebral
           Slopes Using Deep Neural Network

    • Abstract: Objective. To develop a computer-aided method that reduces the variability of Cobb angle measurement for scoliosis assessment. Methods. A deep neural network (DNN) was trained with vertebral patches extracted from spinal model radiographs. The Cobb angle of the spinal curve was calculated automatically from the vertebral slopes predicted by the DNN. Sixty-five in vivo radiographs and 40 model radiographs were analyzed. An experienced surgeon performed manual measurements on the aforementioned radiographs. Two examiners used both the proposed and the manual measurement methods to analyze the aforementioned radiographs. Results. For model radiographs, the intraclass correlation coefficients were greater than 0.98, and the mean absolute differences were less than 3°. This indicates that the proposed system showed high repeatability for measurements of model radiographs. For the in vivo radiographs, the reliabilities were lower than those from the model radiographs, and the differences between the computer-aided measurement and the manual measurement by the surgeon were higher than 5°. Conclusion. The variability of Cobb angle measurements can be reduced if the DNN system is trained with enough vertebral patches. Training data of in vivo radiographs must be included to improve the performance of DNN. Significance. Vertebral slopes can be predicted by DNN. The computer-aided system can be used to perform automatic measurements of Cobb angle, which is used to make reliable and objective assessments of scoliosis.
      PubDate: Tue, 03 Oct 2017 00:00:00 +000
       
  • An Automatic Image Processing System for Glaucoma Screening

    • Abstract: Horizontal and vertical cup to disc ratios are the most crucial parameters used clinically to detect glaucoma or monitor its progress and are manually evaluated from retinal fundus images of the optic nerve head. Due to the rarity of the glaucoma experts as well as the increasing in glaucoma’s population, an automatically calculated horizontal and vertical cup to disc ratios (HCDR and VCDR, resp.) can be useful for glaucoma screening. We report on two algorithms to calculate the HCDR and VCDR. In the algorithms, level set and inpainting techniques were developed for segmenting the disc, while thresholding using Type-II fuzzy approach was developed for segmenting the cup. The results from the algorithms were verified using the manual markings of images from a dataset of glaucomatous images (retinal fundus images for glaucoma analysis (RIGA dataset)) by six ophthalmologists. The algorithm’s accuracy for HCDR and VCDR combined was 74.2%. Only the accuracy of manual markings by one ophthalmologist was higher than the algorithm’s accuracy. The algorithm’s best agreement was with markings by ophthalmologist number 1 in 230 images (41.8%) of the total tested images.
      PubDate: Tue, 29 Aug 2017 07:49:40 +000
       
  • Quantitative Evaluation of Temporal Regularizers in Compressed Sensing
           Dynamic Contrast Enhanced MRI of the Breast

    • Abstract: Purpose. Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is used in cancer imaging to probe tumor vascular properties. Compressed sensing (CS) theory makes it possible to recover MR images from randomly undersampled -space data using nonlinear recovery schemes. The purpose of this paper is to quantitatively evaluate common temporal sparsity-promoting regularizers for CS DCE-MRI of the breast. Methods. We considered five ubiquitous temporal regularizers on 4.5x retrospectively undersampled Cartesian in vivo breast DCE-MRI data: Fourier transform (FT), Haar wavelet transform (WT), total variation (TV), second-order total generalized variation (), and nuclear norm (NN). We measured the signal-to-error ratio (SER) of the reconstructed images, the error in tumor mean, and concordance correlation coefficients (CCCs) of the derived pharmacokinetic parameters (volume transfer constant) and (extravascular-extracellular volume fraction) across a population of random sampling schemes. Results. NN produced the lowest image error (SER: 29.1), while produced the most accurate (CCC: 0.974/0.974) and (CCC: 0.916/0.917). WT produced the highest image error (SER: 21.8), while FT produced the least accurate (CCC: 0.842) and (CCC: 0.799). Conclusion. should be used as temporal constraints for CS DCE-MRI of the breast.
      PubDate: Mon, 28 Aug 2017 00:00:00 +000
       
  • An Automatic Gastrointestinal Polyp Detection System in Video Endoscopy
           Using Fusion of Color Wavelet and Convolutional Neural Network Features

    • Abstract: Gastrointestinal polyps are considered to be the precursors of cancer development in most of the cases. Therefore, early detection and removal of polyps can reduce the possibility of cancer. Video endoscopy is the most used diagnostic modality for gastrointestinal polyps. But, because it is an operator dependent procedure, several human factors can lead to misdetection of polyps. Computer aided polyp detection can reduce polyp miss detection rate and assists doctors in finding the most important regions to pay attention to. In this paper, an automatic system has been proposed as a support to gastrointestinal polyp detection. This system captures the video streams from endoscopic video and, in the output, it shows the identified polyps. Color wavelet (CW) features and convolutional neural network (CNN) features of video frames are extracted and combined together which are used to train a linear support vector machine (SVM). Evaluations on standard public databases show that the proposed system outperforms the state-of-the-art methods, gaining accuracy of 98.65%, sensitivity of 98.79%, and specificity of 98.52%.
      PubDate: Mon, 14 Aug 2017 00:00:00 +000
       
  • Corrigendum to “Automated Feature Extraction in Brain Tumor by Magnetic
           Resonance Imaging Using Gaussian Mixture Models”

    • PubDate: Sun, 13 Aug 2017 08:33:07 +000
       
  • An Improved Extrapolation Scheme for Truncated CT Data Using 2D
           Fourier-Based Helgason-Ludwig Consistency Conditions

    • Abstract: We improve data extrapolation for truncated computed tomography (CT) projections by using Helgason-Ludwig (HL) consistency conditions that mathematically describe the overlap of information between projections. First, we theoretically derive a 2D Fourier representation of the HL consistency conditions from their original formulation (projection moment theorem), for both parallel-beam and fan-beam imaging geometry. The derivation result indicates that there is a zero energy region forming a double-wedge shape in 2D Fourier domain. This observation is also referred to as the Fourier property of a sinogram in the previous literature. The major benefit of this representation is that the consistency conditions can be efficiently evaluated via 2D fast Fourier transform (FFT). Then, we suggest a method that extrapolates the truncated projections with data from a uniform ellipse of which the parameters are determined by optimizing these consistency conditions. The forward projection of the optimized ellipse can be used to complete the truncation data. The proposed algorithm is evaluated using simulated data and reprojections of clinical data. Results show that the root mean square error (RMSE) is reduced substantially, compared to a state-of-the-art extrapolation method.
      PubDate: Thu, 20 Jul 2017 00:00:00 +000
       
  • Corrigendum to “Automatic Characterization of the Physiological
           Condition of the Carotid Artery in 2D Ultrasound Image Sequences Using
           Spatiotemporal and Spatiospectral 2D Maps”

    • PubDate: Wed, 28 Jun 2017 00:00:00 +000
       
  • Intraoperative Imaging Modalities and Compensation for Brain Shift in
           Tumor Resection Surgery

    • Abstract: Intraoperative brain shift during neurosurgical procedures is a well-known phenomenon caused by gravity, tissue manipulation, tumor size, loss of cerebrospinal fluid (CSF), and use of medication. For the use of image-guided systems, this phenomenon greatly affects the accuracy of the guidance. During the last several decades, researchers have investigated how to overcome this problem. The purpose of this paper is to present a review of publications concerning different aspects of intraoperative brain shift especially in a tumor resection surgery such as intraoperative imaging systems, quantification, measurement, modeling, and registration techniques. Clinical experience of using intraoperative imaging modalities, details about registration, and modeling methods in connection with brain shift in tumor resection surgery are the focuses of this review. In total, 126 papers regarding this topic are analyzed in a comprehensive summary and are categorized according to fourteen criteria. The result of the categorization is presented in an interactive web tool. The consequences from the categorization and trends in the future are discussed at the end of this work.
      PubDate: Mon, 05 Jun 2017 08:15:54 +000
       
  • Monte Carlo Simulation for Polychromatic X-Ray Fluorescence Computed
           Tomography with Sheet-Beam Geometry

    • Abstract: X-ray fluorescence computed tomography (XFCT) based on sheet beam can save a huge amount of time to obtain a whole set of projections using synchrotron. However, it is clearly unpractical for most biomedical research laboratories. In this paper, polychromatic X-ray fluorescence computed tomography with sheet-beam geometry is tested by Monte Carlo simulation. First, two phantoms ( and ) filled with PMMA are used to simulate imaging process through GEANT 4. Phantom contains several GNP-loaded regions with the same size (10 mm) in height and diameter but different Au weight concentration ranging from 0.3% to 1.8%. Phantom contains twelve GNP-loaded regions with the same Au weight concentration (1.6%) but different diameter ranging from 1 mm to 9 mm. Second, discretized presentation of imaging model is established to reconstruct more accurate XFCT images. Third, XFCT images of phantoms and are reconstructed by filter back-projection (FBP) and maximum likelihood expectation maximization (MLEM) with and without correction, respectively. Contrast-to-noise ratio (CNR) is calculated to evaluate all the reconstructed images. Our results show that it is feasible for sheet-beam XFCT system based on polychromatic X-ray source and the discretized imaging model can be used to reconstruct more accurate images.
      PubDate: Mon, 08 May 2017 09:44:10 +000
       
  • Fast Compressed Sensing MRI Based on Complex Double-Density Dual-Tree
           Discrete Wavelet Transform

    • Abstract: Compressed sensing (CS) has been applied to accelerate magnetic resonance imaging (MRI) for many years. Due to the lack of translation invariance of the wavelet basis, undersampled MRI reconstruction based on discrete wavelet transform may result in serious artifacts. In this paper, we propose a CS-based reconstruction scheme, which combines complex double-density dual-tree discrete wavelet transform (CDDDT-DWT) with fast iterative shrinkage/soft thresholding algorithm (FISTA) to efficiently reduce such visual artifacts. The CDDDT-DWT has the characteristics of shift invariance, high degree, and a good directional selectivity. In addition, FISTA has an excellent convergence rate, and the design of FISTA is simple. Compared with conventional CS-based reconstruction methods, the experimental results demonstrate that this novel approach achieves higher peak signal-to-noise ratio (PSNR), larger signal-to-noise ratio (SNR), better structural similarity index (SSIM), and lower relative error.
      PubDate: Sun, 09 Apr 2017 00:00:00 +000
       
  • Phase Segmentation Methods for an Automatic Surgical Workflow Analysis

    • Abstract: In this paper, we present robust methods for automatically segmenting phases in a specified surgical workflow by using latent Dirichlet allocation (LDA) and hidden Markov model (HMM) approaches. More specifically, our goal is to output an appropriate phase label for each given time point of an SW in an operating room. The fundamental idea behind our work lies in constructing an HMM based on observed values obtained via an LDA topic model covering optical flow motion features of general working contexts, including medical staff, equipment, and materials. We have an awareness of such working contexts by using multiple synchronized cameras to capture the surgical workflow. Further, we validate the robustness of our methods by conducting experiments involving up to 12 phases of surgical workflows with the average length of each surgical workflow being 12.8 minutes. The maximum average accuracy achieved after applying leave-one-out cross-validation was 84.4%, which we found to be a very promising result.
      PubDate: Sun, 19 Mar 2017 00:00:00 +000
       
  • A Novel Histogram Region Merging Based Multithreshold Segmentation
           Algorithm for MR Brain Images

    • Abstract: Multithreshold segmentation algorithm is time-consuming, and the time complexity will increase exponentially with the increase of thresholds. In order to reduce the time complexity, a novel multithreshold segmentation algorithm is proposed in this paper. First, all gray levels are used as thresholds, so the histogram of the original image is divided into 256 small regions, and each region corresponds to one gray level. Then, two adjacent regions are merged in each iteration by a new designed scheme, and a threshold is removed each time. To improve the accuracy of the merger operation, variance and probability are used as energy. No matter how many the thresholds are, the time complexity of the algorithm is stable at . Finally, the experiment is conducted on many MR brain images to verify the performance of the proposed algorithm. Experiment results show that our method can reduce the running time effectively and obtain segmentation results with high accuracy.
      PubDate: Thu, 16 Mar 2017 07:11:37 +000
       
  • Image Analysis for MRI Based Brain Tumor Detection and Feature Extraction
           Using Biologically Inspired BWT and SVM

    • Abstract: The segmentation, detection, and extraction of infected tumor area from magnetic resonance (MR) images are a primary concern but a tedious and time taking task performed by radiologists or clinical experts, and their accuracy depends on their experience only. So, the use of computer aided technology becomes very necessary to overcome these limitations. In this study, to improve the performance and reduce the complexity involves in the medical image segmentation process, we have investigated Berkeley wavelet transformation (BWT) based brain tumor segmentation. Furthermore, to improve the accuracy and quality rate of the support vector machine (SVM) based classifier, relevant features are extracted from each segmented tissue. The experimental results of proposed technique have been evaluated and validated for performance and quality analysis on magnetic resonance brain images, based on accuracy, sensitivity, specificity, and dice similarity index coefficient. The experimental results achieved 96.51% accuracy, 94.2% specificity, and 97.72% sensitivity, demonstrating the effectiveness of the proposed technique for identifying normal and abnormal tissues from brain MR images. The experimental results also obtained an average of 0.82 dice similarity index coefficient, which indicates better overlap between the automated (machines) extracted tumor region with manually extracted tumor region by radiologists. The simulation results prove the significance in terms of quality parameters and accuracy in comparison to state-of-the-art techniques.
      PubDate: Mon, 06 Mar 2017 06:35:32 +000
       
  • Medical Image Fusion Based on Feature Extraction and Sparse Representation

    • Abstract: As a novel multiscale geometric analysis tool, sparse representation has shown many advantages over the conventional image representation methods. However, the standard sparse representation does not take intrinsic structure and its time complexity into consideration. In this paper, a new fusion mechanism for multimodal medical images based on sparse representation and decision map is proposed to deal with these problems simultaneously. Three decision maps are designed including structure information map (SM) and energy information map (EM) as well as structure and energy map (SEM) to make the results reserve more energy and edge information. SM contains the local structure feature captured by the Laplacian of a Gaussian (LOG) and EM contains the energy and energy distribution feature detected by the mean square deviation. The decision map is added to the normal sparse representation based method to improve the speed of the algorithm. Proposed approach also improves the quality of the fused results by enhancing the contrast and reserving more structure and energy information from the source images. The experiment results of 36 groups of CT/MR, MR-T1/MR-T2, and CT/PET images demonstrate that the method based on SR and SEM outperforms five state-of-the-art methods.
      PubDate: Tue, 21 Feb 2017 00:00:00 +000
       
  • Future of the Renal Biopsy: Time to Change the Conventional Modality Using
           Nanotechnology

    • Abstract: At the present time, imaging guided renal biopsy is used to provide diagnoses in most types of primary and secondary renal diseases. It has been claimed that renal biopsy can provide a link between diagnosis of renal disease and its pathological conditions. However, sometimes there is a considerable mismatch between patient renal outcome and pathological findings in renal biopsy. This is the time to address some new diagnostic methods to resolve the insufficiency of conventional percutaneous guided renal biopsy. Nanotechnology is still in its infancy in renal imaging; however, it seems that it is the next step in renal biopsy, providing solutions to the limitations of conventional modalities.
      PubDate: Sun, 19 Feb 2017 00:00:00 +000
       
  • Sparse Codebook Model of Local Structures for Retrieval of Focal Liver
           Lesions Using Multiphase Medical Images

    • Abstract: Characterization and individual trait analysis of the focal liver lesions (FLL) is a challenging task in medical image processing and clinical site. The character analysis of a unconfirmed FLL case would be expected to benefit greatly from the accumulated FLL cases with experts’ analysis, which can be achieved by content-based medical image retrieval (CBMIR). CBMIR mainly includes discriminated feature extraction and similarity calculation procedures. Bag-of-Visual-Words (BoVW) (codebook-based model) has been proven to be effective for different classification and retrieval tasks. This study investigates an improved codebook model for the fined-grained medical image representation with the following three advantages: (1) instead of SIFT, we exploit the local patch (structure) as the local descriptor, which can retain all detailed information and is more suitable for the fine-grained medical image applications; (2) in order to more accurately approximate any local descriptor in coding procedure, the sparse coding method, instead of -means algorithm, is employed for codebook learning and coded vector calculation; (3) we evaluate retrieval performance of focal liver lesions (FLL) using multiphase computed tomography (CT) scans, in which the proposed codebook model is separately learned for each phase. The effectiveness of the proposed method is confirmed by our experiments on FLL retrieval.
      PubDate: Mon, 13 Feb 2017 00:00:00 +000
       
  • Image Retrieval Method for Multiscale Objects from Optical Colonoscopy
           Images

    • Abstract: Optical colonoscopy is the most common approach to diagnosing bowel diseases through direct colon and rectum inspections. Periodic optical colonoscopy examinations are particularly important for detecting cancers at early stages while still treatable. However, diagnostic accuracy is highly dependent on both the experience and knowledge of the medical doctor. Moreover, it is extremely difficult, even for specialist doctors, to detect the early stages of cancer when obscured by inflammations of the colonic mucosa due to intractable inflammatory bowel diseases, such as ulcerative colitis. Thus, to assist the UC diagnosis, it is necessary to develop a new technology that can retrieve similar cases of diagnostic target image from cases in the past that stored the diagnosed images with various symptoms of colonic mucosa. In order to assist diagnoses with optical colonoscopy, this paper proposes a retrieval method for colonoscopy images that can cope with multiscale objects. The proposed method can retrieve similar colonoscopy images despite varying visible sizes of the target objects. Through three experiments conducted with real clinical colonoscopy images, we demonstrate that the method is able to retrieve objects of any visible size and any location at a high level of accuracy.
      PubDate: Wed, 01 Feb 2017 00:00:00 +000
       
 
 
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