Rangaraj M. Rangayyan

The University of Calgary, Calgary, Alberta, Canada

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Publications (336)294.01 Total impact

  • P. Casti · A. Mencattini · M. Salmeri · A. Ancona · F. Mangeri · M.L. Pepe · R.M. Rangayyan
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    ABSTRACT: We present a multistage approach to detection and classification of mammographic lesions that is independent of accurate extraction of their contours. The ultimate goal is to discriminate malignant tumors from benign lesions and normal parenchymal tissue in a realistic scenario of lesion candidates automatically detected in mammograms. Local analysis of the Gaussian curvature and of the phase response of multidirectional Gabor filters is performed for identification of suspicious focal areas. The detection of lesions and the classification of malignant tumors are performed in series, respectively, via a differential approach to analysis of the tissue surrounding the candidates and via quantification of nonstationarity and spatial dependence of pixel values within circular and annular regions of interest. A unified 3D free-response receiver operating characteristic framework is applied for global analysis of the two binary categorization problems in series. The system was tested on a total of 2105 full-field digital and screen-film mammograms from three different datasets, including abnormal mammograms with 560 malignant tumors and 639 benign lesions, masses, or architectural distortion, and 1010 normal mammograms. For sensitivity of detection of malignant tumors in the range of 0.70-0.81, the range of falsely detected malignant tumors was 0.82-3.47 per image, with a series of two stages of classification, including stepwise logistic regression for selection of features, Fisher linear discriminant analysis, and two-fold cross-validation.
    No preview · Article · Mar 2016 · Biomedical Signal Processing and Control
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    ABSTRACT: This paper presents a new method consisting of two stages for automatic detection and segmentation of coronary arteries in X-ray angiograms. In the first stage, multiscale Gabor filters are used to detect vessel structures in the angiograms. The results of multiscale Gabor filtering are compared with those obtained by applying multiscale methods based on the top-hat operator, Hessian matrix, and Gaussian matched filters. The performance of the vessel-detection methods is evaluated through the area (Az) under the receiver operating characteristic (ROC) curve. In the second stage, coronary arteries are segmented by binarizing the magnitude response of Gabor filters using a new thresholding method based on multiobjective optimization, which is compared with seven thresholding methods. Measures of sensitivity, specificity, accuracy, and positive predictive value are used to analyze the segmentation methods, by comparing the results to the ground-truth markings of the vessels drawn by a specialist. Finally, the proposed method is compared with seven state-of-the-art vessel segmentation methods. The result of vessel detection using multiscale Gabor filters demonstrated high accuracy with Az = 0.961 with a training set of 40 angiograms and Az = 0.952 with an independent test set of 40 angiograms. The results of vessel segmentation with the multiobjective thresholding method provided an average accuracy of 0.881 with the test set of angiograms.
    No preview · Article · Mar 2016 · Biomedical Signal Processing and Control
  • Mario Mustra · Mislav Grgic · Rangaraj M Rangayyan
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    ABSTRACT: This paper presents a review of recent advances in the development of methods for segmentation of the breast boundary and the pectoral muscle in mammograms. Regardless of improvement of imaging technology, accurate segmentation of the breast boundary and detection of the pectoral muscle are still challenging tasks for image processing algorithms. In this paper, we discuss problems related to mammographic image preprocessing and accurate segmentation. We review specific methods that were commonly used in most of the techniques proposed for segmentation of mammograms and discuss their advantages and disadvantages. Comparative analysis of the methods reported on is made difficult by variations in the datasets and procedures of evaluation used by the authors. We attempt to overcome some of these limitations by trying to compare methods which used the same dataset and have some similarities in approaches to the breast boundary segmentation and detection of the pectoral muscle. In this paper, we will address the most often used methods for segmentation such as thresholding, morphology, region growing, active contours, and wavelet filtering. These methods, or their combinations, are the ones most used in the last decade by the majority of work published in this image processing domain.
    No preview · Article · Nov 2015 · Medical & Biological Engineering
  • Faraz Oloumi · Rangaraj M. Rangayyan · Paola Casti · Anna L. Ells
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    ABSTRACT: Changes in the characteristics of retinal vessels such as width and tortuosity can be signs of the presence of several diseases such retinopathy of prematurity (ROP) and diabetic retinopathy. Plus disease is an indicator of ROP which requires treatment and is signified by an increase in posterior venular width. In this work, we present image processing techniques for the detection, segmentation, tracking, and measurement of the width of the major temporal arcade (MTA), which is the thickest venular branch in the retina. Several image processing techniques have been employed, including the use of Gabor filters to detect the MTA, morphological image processing to obtain its skeleton, Canny׳s method to detect and select MTA vessel-edge candidates, least-squares fitting to interpolate the MTA edges, and geometrical procedures to measure the width of the MTA. The results, obtained using 110 retinal fundus images of preterm infants, indicate a statistically highly significant difference in MTA width of normal cases as compared to cases with plus disease (p<0.01). The results provide good accuracy in computer-aided diagnosis (CAD) of plus disease with an area under the receiver operating characteristic curve of 0.76. The proposed methods may be used in CAD of plus disease and timely treatment of ROP in a clinical or teleophthalmological setting.
    No preview · Article · Sep 2015 · Computers in Biology and Medicine
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    ABSTRACT: Fractures with partial collapse of vertebral bodies are generically referred to as "vertebral compression fractures" or VCFs. VCFs can have different etiologies comprising trauma, bone failure related to osteoporosis, or metastatic cancer affecting bone. VCFs related to osteoporosis (benign fractures) and to cancer (malignant fractures) are commonly found in the elderly population. In the clinical setting, the differentiation between benign and malignant fractures is complex and difficult. This paper presents a study aimed at developing a system for computer-aided diagnosis to help in the differentiation between malignant and benign VCFs in magnetic resonance imaging (MRI). We used T1-weighted MRI of the lumbar spine in the sagittal plane. Images from 47 consecutive patients (31 women, 16 men, mean age 63 years) were studied, including 19 malignant fractures and 54 benign fractures. Spectral and fractal features were extracted from manually segmented images of 73 vertebral bodies with VCFs. The classification of malignant vs. benign VCFs was performed using the k-nearest neighbor classifier with the Euclidean distance. Results obtained show that combinations of features derived from Fourier and wavelet transforms, together with the fractal dimension, were able to obtain correct classification rate up to 94.7% with area under the receiver operating characteristic curve up to 0.95.
    Full-text · Conference Paper · Aug 2015
  • E. Almeida · R.M. Rangayyan · P.M. Azevedo-Marques
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    ABSTRACT: This paper presents results of statistical analysis of fractal and texture features obtained from images of diffuse pulmonary diseases (DPDs). The features were extracted from preprocessed regions of interest (ROIs) selected from high-resolution computed tomography images. The ROIs represent five different patterns of DPDs and normal lung tissues. A Gaussian mixture model (GMM) was constructed for each feature, including all patterns. For each GMM, the six classes were identified and compared with the radiological classification of the corresponding ROIs. In 78.5% of the features, the GMM provides, for at least one class, a correct classification of at least 60%. The GMM approach facilitates detailed statistical analysis of the characteristics of each feature and assists in the development of classification strategies.
    No preview · Article · Jun 2015
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    ABSTRACT: Abstract–Our study aimed to develop a system for computer-aided diagnosis of vertebral compression fractures (VCFs) using magnetic resonance imaging (MRI), to help in the differentiation between malignant and benign VCFs. Lumbar spine MRI was used to acquire T1-weighted images in the sagittal plane. Images from 63 consecutive patients (38 women, 25 men, mean age 62.25 ± 14.13 years) with at least one VCF diagnosis were studied. Contrast and texture features were extracted from manually segmented images of 103 vertebral bodies with VCFs. The classification of malignant vs. benign VCFs was performed using the k-nearest neighbor (KNN) classifier with the Euclidean distance. Using a KNN classifier with k=3, feature selection, and 10-fold cross-validation, we obtained a value of the area under the receiver operating characteristic curve of 0.913.
    Full-text · Conference Paper · Jun 2015
  • Antonio Cesar Germano Martins · Rangaraj Mandayam Rangayyan
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    ABSTRACT: We present a procedure based on one-dimensional cepstral filters in the Radon domain to extract texture elements or textons from images with (quasi-) periodic or ordered texture. With this approach, no assumption is required on the homogeneity of the texton. By applying the cepstral filter in the Radon domain, the difficulties associated with two-dimensional cepstral analysis and phase unwrapping are obviated. The necessity of a weighting function as a preprocessing step and details of wavelet extraction in the Radon domain are discussed. The method should facilitate structural analysis of ordered texture and the constituent textons.
    No preview · Article · Mar 2015 · IETE Journal of Research
  • Roseli De Deus Lopes · Rangaraj Mandayam Rangayyan
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    ABSTRACT: We present region-based filters for noise removal in three-dimensional (3D) images in the (x, y, z) domain. The filters start with region growing at each voxel to determine a context-dependent region in 3D. Appropriate selection of region-growing criteria provides regions that approximate 3D objects or features present in the image. Local statistics are then used to filter noise. The method permits adaptive noise removal without degradation of edges, surfaces, or shapes of objects. Results of 3D region-based mean, median, and local linear minimum mean-squared error (LLMMSE) filtering are shown, along with results of two-dimensional (2D) region-based filtering on a slice-by-slice basis, as well as 2D and 3D fixed-neighborhood filtering. Results of 3D region-based filtering possess lower mean-squared errors (MSE) than the results of fixed-neighborhood filters in 3D or 2D. Furthermore, results of 3D region-based filtering possess MSE lower than or equal to the MSE of the results of 2D region-based filtering because 3D filtering exploits the presence of 3D structures in the images. The methods should be applicable in processing of 3D medical images and as a pre-processing step in volume visualization.
    No preview · Article · Mar 2015 · IETE Journal of Research
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    ABSTRACT: Detection of the nipple in mammograms is an important step in algorithms for the detection of breast cancer. However, locating the nipple position is a challenging task due to distortion and displacement of the nipple by breast diseases, improper imaging techniques, and variation of the characteristics of breast tissues with different imaging protocols or modalities. This paper presents a novel approach for the detection of the nipple in mammograms based on the converging characteristics of oriented patterns of the breast tissues towards the nipple. The oriented structures are extracted with a bank of real Gabor filters and are transformed into the Radon domain to analyze linear structures of tissue patterns to determine the nipple position. The performance of the method was evaluated with different types of images, such as scanned screen-film (from the mini-MIAS and DDSM databases), digital radiography, and computed radiography, and average errors of 7.71 mm, 7.52 mm, 9.23 mm, and 12.10 mm were achieved, respectively, with reference to the nipple location marked by an expert radiologist. The proposed method outperforms two recently developed approaches for the same application.
    Full-text · Article · Jan 2015 · Biomedical Signal Processing and Control
  • Faraz Oloumi · Rangaraj M Rangayyan · Anna L Ells
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    ABSTRACT: Purpose: We tested the hypothesis that the openness of the major temporal arcade (MTA) changes in the presence of plus disease, by quantification via parabolic modeling of the MTA, as well as measurement of an arcade angle for comparative analysis. Such analysis could assist in the detection and treatment of progressive retinopathy of prematurity. Methods: Digital image processing techniques were applied for the detection and modeling of the MTA via a graphical user interface (GUI) to quantify the openness of the MTA. An arcade angle measure, based on a previously proposed method, also was obtained via the GUI for comparative analysis. The statistical significance of the differences between the plus and no-plus cases for each parameter was analyzed using the P value. The area (Az) under the receiver operating characteristic curve was used to assess the diagnostic performance of each feature. Results: The temporal arcade angle measure and the openness parameter of the parabolic model were used to perform discrimination of plus versus no-plus cases. Using a set of 19 cases with plus and 91 with no plus disease, Az=0.70 was obtained using the results of dual-parabolic modeling in screening for plus disease. The arcade angle measure provided comparable results with Az=0.73. Conclusions: Using our proposed image analysis techniques and software, this study demonstrates, for the first time to our knowledge, that the openness of the MTA decreases in the presence of plus disease.
    No preview · Article · Aug 2014 · Investigative Ophthalmology & Visual Science
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    ABSTRACT: We present a comprehensive and fully automated system for computer-aided detection and diagnosis of masses in mammograms. Novel methods for detection include: selection of suspicious focal areas based on analysis of the gradient vector field, rejection of oriented components of breast tissue using multidirectional Gabor filtering, and use of differential features for rejection of false positives (FPs) via clustering of the surrounding fibroglandular tissue. The diagnosis step is based on extraction of contour-independent features for characterization of lesions as benign or malignant from automatically detected circular and annular regions. A new unified 3D free-response receiver operating characteristic framework is introduced for global analysis of two binary categorization problems in cascade. In total, 3,080 suspicious focal areas were extracted from a set of 156 full-field digital mammograms, including 26 malignant tumors, 120 benign lesions, and 18 normal mammograms. The proposed system detected and diagnosed malignant tumors with a sensitivity of 0.96, 0.92, and 0.88 at, respectively, 1.83, 0.46, and 0.45 FPs/image, with two stages of stepwise logistic regression for selection of features, a cascade of Fisher linear discriminant analysis and an artificial neural network with radial basis functions, and leave-one-patient-out cross-validation.
    No preview · Article · Aug 2014
  • Faraz Oloumi · Rangaraj M Rangayyan · Anna L Ells
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    ABSTRACT: Diagnosis of plus disease is crucial for timely treatment and management of retinopathy of prematurity. An indicator of the presence of plus disease is an increase in the tortuosity of blood vessels in the retina. In this work, we propose a new angle-variation-based measure for quantification of tortuosity in retinal fundus images of preterm infants. The methods include the use of Gabor filters to detect vessels as well as to obtain their orientation at each pixel. Morphological image processing methods are used to obtain a skeleton image of the vessels for measurement of tortuosity. Out of 11 vessel segments, marked by an expert ophthalmologist as showing high levels of tortuosity due to plus disease, all were correctly identified using the proposed methods.
    No preview · Article · Aug 2014
  • Paola Casti · Arianna Mencattini · Marcello Salmeri · Rangaraj M. Rangayyan
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    ABSTRACT: We present a novel method to detect asymmetry in mammograms based upon bilateral analysis of the spatial distribution of density within paired mammographic strips. Various differential measures of spatial correlation of gray-scale values were computed with reference to the position of the nipple for a set of 128 pairs of mammograms from the Digital Database for Screening Mammography (DDSM). Features were selected by stepwise logistic regression and the leave-one-patient-out method was used for cross-validation of results. An area under the receiver operating characteristic curve of 0.87 (SE = 0.08) was achieved by using an artificial neural network classifier with radial basis functions.
    No preview · Chapter · Jun 2014
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    ABSTRACT: The purpose of this article is to propose the use of fractal and texture analysis for computer-aided diagnosis (CAD) of diffuse pulmonary diseases (DPDs) in high-resolution computed tomography (HRCT) images. We propose multiple techniques to extract features from preprocessed regions of interest (ROIs) selected to represent five radiographic patterns useful in the differential diagnosis of DPDs, as well as normal cases. First-order statistics of gray-level distribution, Haralick's and Laws' texture features, statistical information extracted from the ROIs' discrete Fourier transforms, and their fractal dimension values were used as attributes. The features were used as inputs for a k-nearest neighbor classifier (k=5). With a dataset of 3252 ROIs, correct classification rates of up to 82.62% were achieved.
    No preview · Conference Paper · Jun 2014
  • Faraz Oloumi · Rangaraj M. Rangayyan · Anna L. Ells
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    ABSTRACT: Changes in retinal vessel width can be indicative of the presence of several diseases, such as diabetic retinopathy, retinopathy of prematurity (ROP), and hypertension. Accurate detection and measurement of such changes could help in computer-aided diagnosis. An increase in venular thickness is a sign of plus disease, which warrants treatment of ROP. We present image processing methods for detection, tracking, and measurement of the width of the major temporal arcade (MTA), which is the thickest branch of the venular vessels, in retinal fundus images of preterm infants. The methods include the use of Gabor filters for the detection of the blood vessels, as well as morphological image processing for tracking and measurement of the width of the MTA. The results indicate a statistically significant difference in vessel width of normal cases as compared to cases diagnosed with plus disease (p = 0.015).
    No preview · Conference Paper · Jun 2014
  • E. Y. K. Ng · U. Rajendra Acharya · Rangaraj M. Rangayyan · Jasjit S. Suri

    No preview · Book · May 2014
  • Faraz Oloumi · Rangaraj M. Rangayyan · Anna L. Ells
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    ABSTRACT: Accurate detection of the major temporal arcade (MTA) in retinal fundus images could assist in localization of various anatomical features of the retina, such as the optic nerve head (ONH) and fovea, as well as in detection of certain types of retinopathy. In this paper, we present a novel automated tracking algorithm to obtain a skeleton image representing only the MTA, by detection of the vascular tree using Gabor filters, detection of the center of the ONH using phase portrait analysis, and morphological image processing. The methods were trained and tested using two independent sets of 20 retinal images each. The results were evaluated in terms of the mean distance to the closest point (MDPC) computed for each tracked MTA as compared to its corresponding hand-drawn trace. The test results indicate a low average MDCP error of approximately 2 pixels per MTA skeleton. The proposed algorithm should assist in detection and diagnosis of diseases such as proliferative diabetic retinopathy and retinopathy of prematurity, as well as in localization of the ONH and fovea.
    No preview · Conference Paper · May 2014
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    ABSTRACT: This article describes the development of a quantitative method for computer-aided diagnosis (CAD) of intervertebral disc degeneration according to Pfirrmann's scale, a semiquantitative scale with five degrees of degeneration, in T2-weighted magnetic resonance images of the lumbar spine. The dataset consists of images of 210 discs obtained from 42 healthy individuals. The intervertebral discs were assigned Pfirrmann's grades based on independent and blind classification. Binary masks of manually segmented discs were used to compute the centroids of the regions, estimate the curvature of the spine by polynomial fitting, normalize intensities, and extract regions of interest. Texture analysis was performed using Haralick's features and moments were computed for each disc. Classification was performed using an artificial neural network using the full vectors of attributes as well as a reduced set obtained using gradient ascent search. An average true-positive rate of 75.2% and an average area under the receiver operating characteristic curve of 0.78 indicate potential application of this technique for CAD of spinal pathology.
    Full-text · Conference Paper · May 2014
  • Faraz Oloumi · Rangaraj M. Rangayyan · Anna L. Ells
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    ABSTRACT: The monitoring of the effects of retinopathy on the visual system can be assisted by analyzing the vascular architecture of the retina. This book presents methods based on Gabor filters to detect blood vessels in fundus images of the retina. Forty images of the retina from the Digital Retinal Images for Vessel Extraction (DRIVE) database were used to evaluate the performance of the methods. .e results demonstrate high efficiency in the detection of blood vessels with an area under the receiver operating characteristic curve of 0:96. Monitoring the openness of the major temporal arcade (MTA) could facilitate improved diagnosis and optimized treatment of retinopathy. This book presents methods for the detection and modeling of the MTA, including the generalized Hough transform to detect parabolic forms. Results obtained with 40 images of the DRIVE database, compared with hand-drawn traces of the MTA, indicate a mean distance to the closest point of about 0:24 mm. This book illustrates applications of the methods mentioned above for the analysis of the effects of proliferative diabetic retinopathy and retinopathy of prematurity on retinal vascular architecture.
    No preview · Article · Jan 2014 · Synthesis Lectures on Biomedical Engineering

Publication Stats

5k Citations
294.01 Total Impact Points

Institutions

  • 1988-2016
    • The University of Calgary
      • • Department of Electrical and Computer Engineering
      • • Schulich School of Engineering
      • • Department of Radiology
      • • Sport Medicine Centre
      Calgary, Alberta, Canada
  • 2000-2010
    • Ryerson University
      • Department of Electrical and Computer Engineering
      Toronto, Ontario, Canada
  • 2006-2008
    • Universidade Federal de Uberlândia (UFU)
      • Faculty of Computing (FACOM)
      UDI, Minas Gerais, Brazil
  • 1996-2007
    • University of São Paulo
      • Departamento de Engenharia de Sistemas Eletrônicos (PSI) (POLI)
      San Paulo, São Paulo, Brazil
  • 2001
    • Universidad de Sevilla
      Hispalis, Andalusia, Spain
  • 1989
    • University of Lethbridge
      • Department of Biological Sciences
      Lethbridge, Alberta, Canada