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mammography
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An adaptive filter for noise cancelling in mammography images based on Cellular Automata
, Article International Review on Modelling and Simulations ; Volume 5, Issue 3 , June , 2012 , Pages 1322-1326 ; 19749821 (ISSN) ; Masoumzadeh Tork, A ; Yazdan Talab, E ; Ramezanpour, H ; Darmani, G ; Sharif University of Technology
2012
Abstract
In recent years, several techniques based on repetition of the image are used to remove noise. In this paper a new method based on Cellular Automata for image noise removal in mammography images is recommended. We present a new formulation that makes improvements. The formulation uses a neighborhood with sizes and format adapted to the features of the image on reconstruction. We demonstrated through experiments and comparison with other common used techniques that this procedure produces excellent results for the problem of restoring true color images
Novel margin features for mammographic mass classification
, Article Proceedings - 2012 11th International Conference on Machine Learning and Applications, ICMLA 2012 ; Volume 2 , 2012 , Pages 139-144 ; 9780769549132 (ISBN) ; Zarghami, A ; Manzuri Shalmani, M. T ; Sharif University of Technology
2012
Abstract
Computer-Aided Diagnosis (CAD) systems are widely used for detection of various kinds of abnormalities in mammography images. Masses are one type of these abnormalities which are mostly characterized by their margin and shape. For classification of masses proper features are needed to be extracted. However, the number of well-known features for describing margin is much fewer than geometrical, shape, and textural ones. In addition, most of the existing margin features are highly dependent on segmentation accuracy. In this work, new features for describing margin of masses are presented which can handle inaccuracies in segmentation. These features are obtained from a set of waveforms by...
Design of linear anti-scatter grid geometry with optimum performance for screen-film and digital mammography systems
, Article Physics in Medicine and Biology ; Volume 60, Issue 15 , July , 2015 , Pages 5753-5765 ; 00319155 (ISSN) ; Sohrabpour, M ; Sharif University of Technology
Institute of Physics Publishing
2015
Abstract
A detailed 3D Monte Carlo simulation of the grid geometrical parameters in screen-film mammography (SFM) and digital mammography (DM) systems has been performed. A combination of IEC 60627:2013 international standard conditions and other more clinically relevant parameters were used for this simulation. Accuracy of our results has been benchmarked with previously published data and good agreement has been obtained. Calculations in a wide range of linear anti-scatter grid geometries have been carried out. The evaluated parameters for the SFM system were the Bucky factor (BF) and contrast improvement factor (CIF) and for the DM system it was signal differenceto- noise ratio improvement factor...
Automatic Classification of Masses in Mammographic Images using Sparse Representation
, M.Sc. Thesis Sharif University of Technology ; Manzouri, Mohammad Taghi (Supervisor)
Abstract
Computer Aided Diagnosis (CAD) systems are widely used in different medical tasks. Radiology is a branch of medicine which takes advantage of image processing techniques to help radiologists, analyse complicated radiologic images. Among all kind of medical imagingprocedures, utilization of screening mammographyisgetting very popularin detection of breast abnormalities. A typical CAD system for mammogram analysis uses image enhancement and segmentation as pre-processing phase, and feature extraction and classification for detection phase. In this thesis, we have studied different approaches in each level of image processing required in a mammogram mass classification systems, and introduced a...
Lesion Classification in Mammography Images
, M.Sc. Thesis Sharif University of Technology ; Manzuri Shalmani, Mohammad Taghi (Supervisor)
Abstract
Computer-Aided Diagnosis (CAD) systems are widely used for detection of various kinds of abnormalities in mammography images. In this work, mass classification is investigated and its steps are explained in detail, for each step a main method is presented and other methods are also discussed. For mass segmentation a relatively new method based on level set and Morphological Component Analysis (MCA) is used.After this step, various kinds of features such as shape, geometrical, and textural ones are introduced. Moreover, a set of proposed features based on wavelet transformation,for this application are presented. The proposed features can describe margin and texture characterizations of a...
Content based mammogram image retrieval based on the multiclass visual problem
, Article 2010 17th Iranian Conference of Biomedical Engineering, ICBME 2010 - Proceedings, 3 November 2010 through 4 November 2010, Isfahan ; 2010 ; 9781424474844 (ISBN) ; Fatemizadeh, E ; Sharif University of Technology
2010
Abstract
Since expertise elicited from past resolved cases plays an important role in medical application and images acquired from various cases have a great contribution to diagnosis of the abnormalities, Content based medical image retrieval has become an active research area for many scientists, In this article we proposed a new framework to retrieve visually similar images from a large database, in which visual relevance is regarded as much as the semantic category similarity, we used optimized wavelet transform as the multi-resolution analysis of the images and extracted various statistical SGLDM features from different resolutions then after reducing feature space we used error correcting codes...
Simulation of a PEM (Positron Emission Mammography) System by GATE
, M.Sc. Thesis Sharif University of Technology ; Sohrabpour, Mostafa (Supervisor) ; Setayeshi, Saeed (Co-Advisor)
Abstract
Breast cancer is the second leading cause of cancer death among women. Mammography is considered the “gold standard” in the evaluation of the breast lesions from an imaging perspective. But this modality has limitations. Completed studies are used to overcome these limitations. The Positron Emission Mammography (PEM) is the one of these complementary methods. PEM imaging is a molecular imaging modality for the diagnosis of breast cancer. In this thesis, a commercial PEM system as Naviscan PEM has been simulated using the GATE program. This system consists of two parallel planes of detectors, each detector consists of 12 blocks with 6 × 2 array and each block consists of 169 crystals with 13...
Mamsim: A computational software platform for measuring and optimizing imaging and dosimetry parameters in screen-film and digital mammography systems
, Article 15th IEEE International Symposium on Medical Measurements and Applications, MeMeA 2020, 1 June 2020 through 3 June 2020 ; July , 2020 ; Vahdat, B. V ; Ebrahimi Khankook, A ; Noorvand, M ; IEEE; IEEE Instrumentation and Measurement Society; IEEE Sensors Council Italy Chapter; Politecnica di Bari; Politecnico di Torino; Societa Italiana di Analisi del Movimento in Clinica ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2020
Abstract
The aim of this work is to develop a mammography Monte Carlo MCNP-FBSM based simulation platform called 'MamSim' that is able to model the detailed geometry and physics of commercial screen-film and digital mammography units. This simulation platform is designed to enable the virtual assessment and optimization of mammography protocols and parameters for obtaining the desired image quality while diminishing radiation dose to the patient in both contact and magnification modes. A graphical user interface generates MCNP-FBSM input files for simulating mammography units under various geometries and imaging protocols. We considered the full simulation of all components of mammography procedure...
Content Based Mammogram Image Retrieval Based on the Multiclass Visual Problem
, M.Sc. Thesis Sharif University of Technology ; Fatemizadeh, Emad (Supervisor)
Abstract
In recent years there has been a great effort to enhance the computer-aided diagnosis systems, Since expertise elicited from past resolved cases plays an important role in medical applications, and images acquired from various cases have a great contribution to diagnosis of the abnormalities, Content based medical image retrieval has become an active research area for many scientists. In this project we proposed a new framework to retrieve visually similar images from a large database, in which visual similarity is regarded as much as the semantic category relevance, we used optimized wavelet transform as the multi-resolution analysis of the images and extracted various statistical SGLDM...
Feasibility Study of Improving the Quality of PEM Images by Considering TOF and the DOI Correction
, M.Sc. Thesis Sharif University of Technology ; Hosseini, Abolfazle (Supervisor)
Abstract
Breast cancer is the most common type of cancer in women and the second cause of death among them. The chance of successful treatment would be significantly increased if the disease is diagnosed at its early stages. There are numerous methods to diagnose breast cancer. One of the most important methods is positron emission mammography (PEM).The main aim of this study is to investigate the feasibility of improving PEM images by considering the time of flight corrections and the penetration depth of the rays in the crystals.In this study, a commercial PEM system, Naviscan PEM, is simulated using the GATE software. In the first phase of the study, two opposing planar detectors are used to study...
A two layer texture modeling based on curvelet transform and spiculated lesion filters for recognizing architectural distortion in mammograms
, Article Middle East Conference on Biomedical Engineering, MECBME ; 17 - 20 February , 2014 , pp. 21-24 ; Nadjar, H. S ; Fatemizadeh, E ; Mohammadi, E ; Sharif University of Technology
Abstract
This paper presents a two layer texture modeling method to recognize architectural distortion in mammograms. We propose a method that models a Gaussian mixture on the Curvelet coefficients and the outputs of Spiculated Lesion Filters. The Curvelet transform and the Spiculated Lesion Filters have been applied to extract textural features of mammograms in literature. However the key difference between this study and the previous ones is that in our approach, a Gaussian mixture models the textural features extracted by the Curvelet transform and the Spiculated Lesion Filters. The results of the current study are shown in the form of accuracy and the area under the receiver operating...
An efficient fractal method for detection and diagnosis of breast masses in mammograms
, Article Journal of Digital Imaging ; Vol. 27, issue. 5 , 2014 , pp. 661-669 ; ISSN: 08971889 ; AhmadiNoubari, H ; Fatemizadeh, E ; Khalili, M ; Sharif University of Technology
Abstract
In this paper, we present an efficient fractal method for detection and diagnosis of mass lesion in mammogram which is one of the abnormalities in mammographic images. We used 110 images that were carefully selected by a radiologist, and their abnormalities were also confirmed by biopsy. These images included circumscribed benign, ill-defined, and spiculated malignant masses. Firstly, we discriminated lesions automatically using new fractal dimensions. The results which were examined by different types of breast density showed that the proposed method was able to yield quite satisfactory detection results. Secondly, noting that contours of masses playing the most important role in diagnosis...
Mammograms enhancement using wavelet transform and piecewise linear and nonlinear coefficient mapping
, Article Middle East Conference on Biomedical Engineering, MECBME ; Feb , 2014 , p. 107-110 ; Noubari, H. A ; Fatemizadeh, E ; Rezaee, M ; Khalili, M ; Sharif University of Technology
Abstract
In this paper a multi-scale image enhancement strategy using wavelets as applied to digital mammograms is presented. For multiresolution wavelet analysis redundant dyadic discrete wavelet transform is utilized to allow translation invariance and low resolution enhancement capability. Two alternative nonlinear gain adjustments, piecewise linear and Gaussian form of gain adjustment are used for coefficient modification for the enhancement of subtle details such as microcalcification and low resolution edges of different lesion types. The results of comparing these methods of gain adjustment are presented. This comparing has done by defining new parameters for measuring quality of image based...
A textural approach for recognizing architectural distortion in mammograms
, Article Iranian Conference on Machine Vision and Image Processing, MVIP ; September , 2013 , Pages 136-140 ; 21666776 (ISSN) ; 9781467361842 (ISBN) ; Fatemizadeh, E ; Sheikhzadeh, H ; Khoubani, S ; Sharif University of Technology
IEEE Computer Society
2013
Abstract
Breast cancer is considered as the most important cause of death among women. Architectural distortions are very important signs of breast cancer and early detection of them is a rewarding work. In this paper we propose a method to recognize architectural distortion from normal parenchyma. In our proposed method, appropriate features are extracted by the analysis of oriented textures with the application of orientation component of recent the state-of-the-art local texture descriptor called Monogenic Binary Coding (MBC). In addition, we transform Region of Interests (ROIs) to polar coordinates in order to highlight some specific patterns in mammograms. Various classifiers are used over a set...
Evaluation of Effective Factors on The Mammographic Images Utilizing Monte Carlo Simulation
, M.Sc. Thesis Sharif University of Technology ; Sohrabpour, Mostafa (Supervisor)
Abstract
The Scattered radiation is the principal factor affecting the quality of the digital and screen-film mammography images. The contrast improvement factor and bucky factor which are also referred to as the benefit and risk of the anti-scattered grid cannot be properly assessed without a detailed knowledge of the scattered radiation. In this work the scatter to primary ratio has been calculated and an anti-scatter grid has been designed based on the reduction of the scattered radiation to reduce the patient dose to a minimum level and to improve the image quality simultaneously.The MCNPX 2.6.0 Monte Carlo code has been used to improve the geometry of the anti-scatter grid to both reduce the...
Gradient vector flow snake segmentation of breast lesions in dynamic contrast-enhanced MR images
, Article 2010 17th Iranian Conference of Biomedical Engineering, ICBME 2010 - Proceedings, 3 November 2010 through 4 November 2010, Isfahan ; 2010 ; 9781424474844 (ISBN) ; Fatemizadeh, E ; Gity, M ; Sharif University of Technology
Abstract
The development of computer-aided diagnosis (CAD) for breast magnetic resonance (MR) images has encountered some big challenges. One of these challenges is related to breast lesion segmentation. Accurate segmentation of breast lesions has a vital role in other consequent applications such as feature extraction. Since malignant breast lesions typically appear with irregular borders and shapes in MR images whereas benign masses appear with more regular shapes, and smooth and lobulated borders, it seems that the accurate segmentation of breast lesion borders in MR images are important. To achieve this purpose, we have used the Gradient Vector Flow (GVF) snake segmentation method. This study...
Classification of abnormalities in mammograms by new asymmetric fractal features
, Article Biocybernetics and Biomedical Engineering ; Volume 36, Issue 1 , 2016 , Pages 56-65 ; 02085216 (ISSN) ; Ahmadi Noubari, H ; Fatemizadeh, E ; Khalili, M ; Sharif University of Technology
PWN-Polish Scientific Publishers
2016
Abstract
In this paper we use fractal method for detection and diagnosis of abnormalities in mammograms. We have used 168 images that were carefully selected by a radiologist and their abnormalities were also confirmed by biopsy. These images included asymmetric lesions, architectural distortion, normal tissue and mass lesion where in case of mass lesion they included circumscribed benign, ill-defined and spiculated malignant masses. At first, by using wavelet transform and piecewise linear coefficient mapping, image enhancement were done. Secondly detection of lesions was done by fractal method as a ROI. Since in investigation of breast cancer, it is important that fibroglandular tissues in both...
Monte carlo modeling of magnification mode for quantitative assessment of image quality in mammography systems
, Article 2019 IEEE International Symposium on Medical Measurements and Applications, MeMeA 2019, 26 June 2019 through 28 June 2019 ; 2019 ; 9781538684276 (ISBN) ; Khodajou Chokami, H ; Vosoughi, N ; Noorvand, M ; IEEE; IEEE Instrumentation and Measurement Society; Kadir Has University (KHU); UME ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
Scattered radiations are one of the most important factors in the degradation of the image quality of mammography systems. Some techniques have been proposed for the reduction of such rays. Magnification mode can be done by increasing the air gap which determined by the distance of the breast and image intensifier. It is one of the useful techniques to elevate the produced image quality due to the rejection of scattered photons. Monte Carlo N-Particle eXtended transport code (MCNPX) version 2.7.0 is a software package for the simulation of physical processes. In this work, this computer code is used for analyzing the effects of magnification mode on mammographic image quality. To this...