Providing stable and robust power signals for electrical consumers and apparatuses is the most important responsibility of all electric power providers. Whenever the electric power signals suffer from disturbances which affect their... more
Providing stable and robust power signals for electrical consumers and apparatuses is the most important responsibility of all electric power providers. Whenever the electric power signals suffer from disturbances which affect their quality and consequently peril the safety and right operation of electrical appliances, it is the main task of suppliers to detect and solve such obstacles. For defect prevention and faulty situation treatment caused by power quality disturbances, it is necessary to detect and classifythem in a reliable and guaranteed manner. In this paper, an innovative approach toward confident classification of four distinct types of power quality disturbances is proposed. The proposed method comprises of two main stages. In the first stage, noise resistive and steady features based on a new one dimensional local binary pattern approach are extracted and the desired feature vectors are formed. The second stage devotes to the reliable classification of the feature vectors belonging to the studied power quality disturbances based on conventional neural networks. The evaluation results are implemented in the form of Precision, Recall and F-measure. The F-measure about 91% demonstrates the higher efficiencyand performance of proposed method in comparison to the previously proposed strategies based on discrete wavelet and some statistical features with the same neural network classification.
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Polyp is the name of a colorectal lesion which is created by cells clumping on the lining of the colon. The colorectal polyps can lead to severe illnesses like colon cancer if they are not treated at the early stage of their development.... more
Polyp is the name of a colorectal lesion which is created by cells clumping on the lining of the colon. The colorectal polyps can lead to severe illnesses like colon cancer if they are not treated at the early stage of their development. In current days, there are very many different polyp detection strategies based on biomedical imageries such colon capsule endoscopy (CCE) and optical colonoscopy (OC). The CCE imagery is non-invasive but the quality and resolution of acquired images are low. Moreover, it costs more than OC. So, today OC is the most desired method for detecting colorectal polyps and other lesions besides of its invasiveness. To assist physicians in detecting polyps more accurately and faster, machine learning with biomedical image processing aspect emerges. One of the most the state-of-the-art strategies for polyp detection based on artificial intelligence approach are deep learning (DL) convolutional neural networks (CNNs). As the categorization and grading of poly...
In modern remote sensing procedures, one of the most important issues is to distinguish specific types of land coverage. Discrimination between different land coverages especially in metropolitan surveying is so important that the in... more
In modern remote sensing procedures, one of the most important issues is to distinguish specific types of land coverage. Discrimination between different land coverages especially in metropolitan surveying is so important that the in front civilization projects are basically dependent to them. In this paper, an innovative image processing strategy is employed for distinguishing green lands from other metropolitan areas in aerial imaging. The main purpose of this project is to audit green land areas, either public or private, for forthcoming municipal projects. The proposed method is constituted of four main stages. In the first step, the acquired aerial video frames, even in or offline modes, are converted into static images. In the second and third stages, two distinct pre-processing stages are deployed. The output of these two preprocessing stages is segmented into two parts comprising of green land and other urban areas. The evaluation and experimental results demonstrate the fai...
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Research Interests: Computer Science, Information Technology, Health Sciences, Epidemiology, Histology, and 9 moreMedicine, Demographics, Social Science Research Network, Science Computer, Computer Science and Engineering, Computer Science Information Technology, Demographic Factors, Lichen planopilaris, and Clinical features
Abstract The lack of a flexible analysis model has been introduced as an important issue in different applications like source separation. In this paper, a fixed dimension modified sinusoid model (FD-MSM) is proposed for analysis of all... more
Abstract The lack of a flexible analysis model has been introduced as an important issue in different applications like source separation. In this paper, a fixed dimension modified sinusoid model (FD-MSM) is proposed for analysis of all audible signals consisting of speech, music and their mixtures. Employing the peak picking in Meldomain gives rise to a fixed number of parameters in the proposed FDMSM, which is desired in clustering algorithms like VQ (vector quantization) or GMM (gaussian mixture model), commonly ...
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Ali Reza Bayesteh Tashke, Amir Babaeean2, Kourosh Dadashtabar3, Farid Samsami Khodadad 2Department ofElectrical Engineering Amirkabir University of Technology, Dept. ofElectrical Eng, 15875-4413, Hafez, Tehran, Iran... more
Ali Reza Bayesteh Tashke, Amir Babaeean2, Kourosh Dadashtabar3, Farid Samsami Khodadad 2Department ofElectrical Engineering Amirkabir University of Technology, Dept. ofElectrical Eng, 15875-4413, Hafez, Tehran, Iran 3'4DepartmentofElectrical Engineering ...
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Colorectal lesions known as polyps are one of the diagnostic symptoms for colorectal disease. So, their accurate detection and localization based on a computer-aided diagnosis can assist colonists for prescribing more effective... more
Colorectal lesions known as polyps are one of the diagnostic symptoms for colorectal disease. So, their accurate detection and localization based on a computer-aided diagnosis can assist colonists for prescribing more effective treatments. The computer vision and machine learning methods like pattern recognition and deep learning neural networks are the most popular strategies for automatic polyp detection purpose. The proposed approach in this paper is an innovative deep learning neural network. The proposed network has a novel U-Net architecture. The architecture of proposed network includes fully 3D layers which enable the network to be fed with multi or hyperspectral images or even video streams. Moreover, there is a dice prediction output layer. This type of output layer employs probabilistic approaches and benefits from more accurate prediction abilities. The proposed method is applied to international standard optical colonoscopy datasets known as CVC-ClinicDB, CVC-ColonDB and ETIS-Larib. The implementation and evaluation results demonstrate that the proposed U-Net outperforms other competitive methods for automatic polyp detection based on accuracy, precision, recall and F-Score criteria. The proposed method can assist experts and physicians to localize colonial polyps with more accuracy and speed. In addition, the proposed network can be used on live colonoscopy observations due to its high performance and fast operability.
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Introduction: The demographic of Lichen PlanoPilaris (LPP) among the Iranian population is unknown. The aim of this study is to describe the clinical, demographic, and histopathologic findings of lichen planopilaris in the Iranian... more
Introduction: The demographic of Lichen PlanoPilaris (LPP) among the Iranian population is unknown. The aim of this study is to describe the clinical, demographic, and histopathologic findings of lichen planopilaris in the Iranian population. Method: In this cross-sectional study, all the patients with Lichen planopilaris were referred to the dermatology clinic of Imam Khomeini hospital from 2013 to 2015. Their demographic characteristics, drug histories, onset of disease, and family histories were obtained by written questionnaire. Additionally, this study employed SPSS v.20 as the statistical analysis software. Results: One hundred patients were enrolled in this study. With an average age of 47.11 years, 78% of the patients were female, and 50 of these were housewives. The patients included were often from Tehran with Fars ethnicity. Among these patients, 7 had alopecia areata skin disease, and 10 of them suffered from thyroid disease. Most of the histopathology samples collected ...
Abstract—Automatic and reliable extraction of the minutiae from fingerprint images is a critical process in fingerprint matching and a main preprocess for this stage is Thinning. There are a lot of algorithms for fingerprint thinning... more
Abstract—Automatic and reliable extraction of the minutiae from fingerprint images is a critical process in fingerprint matching and a main preprocess for this stage is Thinning. There are a lot of algorithms for fingerprint thinning procedure. All of the previously proposed thinning methods try to thin every ridge due to the content of its central pixel and then extracting minutiae based on some other algorithms for denoising and preventing false minutiae detections at islands or spurities. If an algorithm could thin fingerprint ridges except unrecoverable corrupted regions and also could eliminate noise, it will be considered as a good thinning one and no additional processes are needed before minutiae extraction. The proposed method of this paper has such abilities. The proposed algorithm is implemented by applying four boxes of matrices; each of them thins ridges due to a specific direction; i.e., diagonal, horizontal and vertical directions. The proposed algorithm also is abl...
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A 3D ultrasound computer tomography (USCT) device with a nearly isotropic and spatially invariant 3D point spread function has been constructed at Institute for Data Processing and Electronic (IPE), Karlsruhe Institute of Technology... more
A 3D ultrasound computer tomography (USCT) device with a nearly isotropic and spatially invariant 3D point spread function has been constructed at Institute for Data Processing and Electronic (IPE), Karlsruhe Institute of Technology (KIT). This device is currently applied in clinical studies for breast cancer screening. In this paper, a new method to develop an automated segmentation algorithm for USCT acquired images is proposed. The method employs distance regularized level set evolutionary (DRLSE) active contours along with surface fitting extrapolation and 3D binary mask generation for fully automatic segmentation outcome. In the first stage of the proposed algorithm, DRLSE is applied to those 3D USCT slice images which contain breast and are less affected by noise and ring artifacts named as Cat2. The DRLSE segmentation results are employed to extrapolate the rest of slice images known as Cat1. To overcome defectively segmented slice images, a 3D binary mask is generated out of...
Automatic grading systems based on histopathological slide images are applied to various types of cancers. To date, cancer scientists and researchers have conducted many experiments to find and evaluate new and innovative automatic cancer... more
Automatic grading systems based on histopathological slide images are applied to various types of cancers. To date, cancer scientists and researchers have conducted many experiments to find and evaluate new and innovative automatic cancer grading systems to accelerate their therapeutic diagnoses and ultimately to enable more efficient prognoses. The previously proposed automatic or computer-aided systems for breast cancer grading, including specializing mitosis counting, suffer from various shortcomings. The most important one is their low efficiency along with high complexity due to the huge amount of features. In this paper, three types of features with more flexibility and less complexity are employed. These features are: completed local binary pattern (CLBP) as textural features, statistical moment entropy (SME) and stiffness matrix (SM) as a mathematical model which includes geometric, morphometric and shape-based features. In the proposed automatic mitosis detection method, th...
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Nowadays, automatic computer-Aided Diagnosis (CAD) systems for grading different types of cancers like breast cancer are very prevalent. These systems employ histopathology slide images acquired by advanced and well-defined digital... more
Nowadays, automatic computer-Aided Diagnosis (CAD) systems for grading different types of cancers like breast cancer are very prevalent. These systems employ histopathology slide images acquired by advanced and well-defined digital scanners. The previously proposed automatic or computer-aided systems for breast cancer grading, especially by counting mitoses, suffer from various types of deficiencies. The most important one is their low efficiency along with high complexity due to the huge amount of features. In this paper, two types of features with more flexibility and less complexity are employed. These features are Completed Local Binary Pattern (CLBP) as textural features and Stiffness Matrix as geometric, morphometric and shape-based features. In the proposed automatic mitosis detection system, these two features are fused with each other. The evaluation results are for histology Dataset H (Hamamatsu Nanozoomer Scanners) provided by Mitos-ICPR2012 contest sponsors. Employing a ...
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Moving object detection from municipal surveillance cameras is an important issue for Intelligent Transportation Systems (ITS) purposes. This paper presents a moving object detection algorithm that is more robust than adaptive Gaussian... more
Moving object detection from municipal surveillance cameras is an important issue for Intelligent Transportation Systems (ITS) purposes. This paper presents a moving object detection algorithm that is more robust than adaptive Gaussian mixture (GMM) model, and provides a novel and practical choice for intelligent video surveillance systems using static cameras. The proposed method comprises of three steps. In the first step, statistical bit maps (BMs) are constructed randomly in a block-wise manner. The second step is assigned to background image construction based on two types of comparisons named as intra and inter block comparative approaches. In the third step, based on the smooth or unsmooth states detection for each block of the original video frames, an update or unmatched process will be applied. The results of proposed method's implementation show its better and more efficient performance than other competitive methods like GMM for live and real time moving object detec...
In recent years, employment of dispatching systems including SCADA in Iranian Regional Electric Companies for automation of power plants, sites and generators has become common and outspread. Such systems comprise of some specific... more
In recent years, employment of dispatching systems including SCADA in Iranian Regional Electric Companies for automation of power plants, sites and generators has become common and outspread. Such systems comprise of some specific equipments such as remote terminal unit (RTU), communication medium and computerized dispatching center. For connecting RTU to computer center, different telecommunication media are employed. These media can be power line carrier (PLC), fiber optic and other conventional communication methods. In some cases, there is no way to employ the named communication methods due to unavailability of essential media. In such cases, it is necessary that a new communication strategy be established. In this paper, two new strategies for providing possible data transmission are proposed. For the first solution, a two-way communication over serial to Ethernet conversion base on static IP is proposed. In the first strategy, the communication is provided through asynchronou...
Introduction: The demographic of Lichen PlanoPilaris (LPP) among the Iranian population is unknown. The aim of this study is to describe the clinical, demographic, and histopathologic findings of lichen planopilaris in the Iranian... more
Introduction: The demographic of Lichen PlanoPilaris (LPP) among the Iranian population is unknown. The aim of this study is to describe the clinical, demographic, and histopathologic findings of lichen planopilaris in the Iranian population. Method: In this cross-sectional study, all the patients with Lichen planopilaris were referred to the dermatology clinic of Imam Khomeini hospital from 2013 to 2015. Their demographic characteristics, drug histories, onset of disease, and family histories were obtained by written questionnaire. Additionally, this study employed SPSS v.20 as the statistical analysis software. Results: One hundred patients were enrolled in this study. With an average age of 47.11 years, 78% of the patients were female, and 50 of these were housewives. The patients included were often from Tehran with Fars ethnicity. Among these patients, 7 had alopecia areata skin disease, and 10 of them suffered from thyroid disease. Most of the histopathology samples collected from these biopsies revealed degeneration of the basal layer of the follicular structure, perifollicular fibrosis, inflammatory cells, and atrophy of the pilosebaceous structures. Conclusion: Both the age spectrum and the disease distribution of LPP among the Iranian population were very diverse when compared to previous studies.
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ABSTRACT This paper proposes a lossless data hiding (LDH) scheme on uncompressed video data based on a multi-level histogram shifting mechanism in integer wavelet transform (IWT) domain. The proposed method enables the exact recovery of... more
ABSTRACT This paper proposes a lossless data hiding (LDH) scheme on uncompressed video data based on a multi-level histogram shifting mechanism in integer wavelet transform (IWT) domain. The proposed method enables the exact recovery of the original host signal upon extracting the embedded information, if the watermarked image is not affected by any other process. In the proposed scheme, the approximation subband image of the luminance component of a video frame is computed. Then, it is divided into non overlapping blocks. In each block, the differences between the neighboring elements are computed and a histogram is made on the difference values. The secret data are embedded into the blocks based on a multi-level shifting mechanism of the histogram. Experimental results show that proposed scheme can hide a large amount of information within a video frame with a high degree of robustness against H.264/AVC encoding.
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Abstract As fingerprint verification depends strongly on the quality of fingerprint ridge orientation estimation, so the more accurate fingerprint ridge orientations estimate, the better verification will result in. In this paper, we have... more
Abstract As fingerprint verification depends strongly on the quality of fingerprint ridge orientation estimation, so the more accurate fingerprint ridge orientations estimate, the better verification will result in. In this paper, we have proposed a new technique for improving ...
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AbstractMatching is an important step in any fingerprint recognition system. In this paper, a fingerprint matching technique based on hidden markov model is proposed. This method uses only the ridge orientation information around the... more
AbstractMatching is an important step in any fingerprint recognition system. In this paper, a fingerprint matching technique based on hidden markov model is proposed. This method uses only the ridge orientation information around the reference point of registered fingerprint ...
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Histopathology slides are one of the most applicable resources for pathology studies. As observation of these kinds of slides even by skillful pathologists is a tedious and time-consuming activity, computerizing this procedure aids the... more
Histopathology slides are one of the most applicable resources for pathology studies. As observation of these kinds of slides even by skillful pathologists is a tedious and time-consuming activity, computerizing this procedure aids the experts to have faster analysis with more case studies per day. In this paper, an automatic mitosis detection system (AMDS) for breast cancer histopathological slide images is proposed. In the proposed AMDS, the general phases of an automatic image based analyzer are considered and in each phase, some special innovations are employed. In the pre-processing step to segment the input digital histopathology images more precisely, 2D anisotropic diffusion filters are applied to them. In the training segmentation phase, the histopathological slide images are segmented based on RGB contents of their pixels using maximum likelihood estimation. Then, the mitosis and non-mitosis candidates are processed and hence that their completed local binary patterns are ...
ABSTRACT The privacy and integrity protection of digital documents specially the case of biomedical images is a vital subject in the current world of telecommunication and digital multimedia exchanges. In this paper, a modified semi... more
ABSTRACT The privacy and integrity protection of digital documents specially the case of biomedical images is a vital subject in the current world of telecommunication and digital multimedia exchanges. In this paper, a modified semi robust digital image watermarking method with tamper detection and recovery ability is proposed. For this purpose, the proposed method comprises two stages. In the first stage, a specific order of the integer wavelet coefficient of the original image forms the watermark which prepares both tamper detection and recovery ability. These abilities are created by a specific parsing of watermark bits named as dual watermarking. In the second stage of the proposed method, watermark embedding and extraction procedures are done. To be more robust, a Convolutional Error Correction Code is employed in the watermark establishment process. In the extraction process, the probable tamper will be detected and the original image shall be recovered. This method is also improved to be adopted for reversible ROI recovery of medical images even in the presence of some kind of intentional and unintentional attacks. The experimental results show that the proposed method has a high performance in the case of tamper detection and is able to recover original images from noisy ones.
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ABSTRACT Study of histopathological cancerous tissue is one of the most reliable ways to grade various types of cancers. The result of grading helps the physicians to diagnose and prescribe suitable prognosis. The focus of this paper is... more
ABSTRACT Study of histopathological cancerous tissue is one of the most reliable ways to grade various types of cancers. The result of grading helps the physicians to diagnose and prescribe suitable prognosis. The focus of this paper is on a CAD for automatic analysis of breast cancer histopathological Images to count mitosis as an important criteria for the breast cancer grading. To achieve this aim, sets of specific digital histopathological data are used which are captured by particular microscopic scanners named as Aperio XT and Hamamatsu NanoZoomer scanners. In the proposed method, these acquired images are employed and processed based on digital image processing approaches like 2-D anisotropic diffusion as a pre-process and morphological process. For extraction of pixel-wise features from predetermined mitotic regions, an statistical approach based on color information such as maximum likelihood estimation is employed. To prevent misclassification of mitosis and non-mitosis objects, an object-wise completed local binary pattern (CLBP) is proposed to extract texture features robust against rotation and color-level changes, and finally support vector machine (SVM) is used to classify the extracted feature vectors. Having computed the evaluation criteria, our proposed method performs better f-measure (70.94% for Aperio XT scanner images and 70.11% for Hamamatsu images) among the methods proposed by other participants at ICPR2012 Mitosis detection in breast cancer histopathological images.
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Page 1. A Conditional Selection of Orthogonal Legendre/Chebyshev Polynomials As a Novel Fingerprint Orientation Estimation Smoothing Method Ashkan Tashk*, Mohammad Sadegh Helfroush**, Mohammad Javad Dehghani ...
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ABSTRACT Automatic grading systems based on histopathological slide images are applied to various types of cancers. To date, cancer scientists and researchers have conducted many experiments to find and evaluate new and innovative... more
ABSTRACT Automatic grading systems based on histopathological slide images are applied to various types of cancers. To date, cancer scientists and researchers have conducted many experiments to find and evaluate new and innovative automatic cancer grading systems to accelerate their therapeutic diagnoses and ultimately to enable more efficient prognoses. The previously proposed automatic or computer-aided systems for breast cancer grading, including specializing mitosis counting, suffer from various shortcomings. The most important one is their low efficiency along with high complexity due to the huge amount of features. In this paper, three types of features with more flexibility and less complexity are employed. These features are: completed local binary pattern (CLBP) as textural features, statistical moment entropy (SME) and stiffness matrix (SM) as a mathematical model which includes geometric, morphometric and shape-based features. In the proposed automatic mitosis detection method, these three types of features are fused with each other. The SM feature comprises of characteristics which are to be extracted for reliable discrimination of mitosis objects from non-mitosis ones. The evaluations are applied over histology Datasets A and H provided by the Mitos-ICPR2012 contest sponsors. Employing both a nonlinear radial basis function (RBF) kernel for support vector machine (SVM) and also random forest classifiers, leads to the best efficiencies among the other competitive methods which have been proposed in the past. The results are in the form of F-measure criterion which is a basis for bioinformatics assessments and evaluation.
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ABSTRACT Traffic control systems such as traffic lights play an inevitable role in the current world's transportation guidance and driving fluency. In this paper, an automatic traffic control system based on advance software... more
ABSTRACT Traffic control systems such as traffic lights play an inevitable role in the current world's transportation guidance and driving fluency. In this paper, an automatic traffic control system based on advance software architecture is proposed. In the proposed architecture, automatic car plate recognition and driver verification based on fingerprint biometric are mixed with each other. The license plate recognition part is adapted for Persian or Farsi characters. The persian or farsi characters recognition is done by a very simple Normalized cross correlation which is very analogous to Euclidian distance criterion. To improve the functionality of this platform, some special and innovative digital image processing are employed so that the program is able to extract and recognize the car plate and its related characters even if in the low light or shiny conditions. The fingerprint recognition system is also added to the proposed traffic control system to ensure the authority of the car driver to enter to the places with high privacy and security limitations. The simulation results demonstrate the efficiency and suitable performance of the proposed automatic traffic control system.
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ABSTRACT There are many proposed methods for active sonar target echo detection in reverberation background via either optimal or suboptimal signal processing procedures. Among such methods, those ones which are based on mere filtering,... more
ABSTRACT There are many proposed methods for active sonar target echo detection in reverberation background via either optimal or suboptimal signal processing procedures. Among such methods, those ones which are based on mere filtering, e.g. matched filter, are both efficient and flexible, but suffer from some deficiencies such as high computational complexity or more additional requirements for post-processing. In this paper, an adaptively order-selected pre-whiten filtering method based on autoregressive (AR) modeling of the reverberation data at the active sonar receiving hydrophone is proposed. This method is able to overcome the deficiencies of former filtering methods. This is achieved by applying an AR pre-whiten filter that has its order selected adaptively using data partitioning. The adaptive order selection of AR pre-whiten filter is done by the use of FPEF which is a high performance AR order selection criterion. The results of simulation show that the proposed method is more efficient than the previously proposed order/reverse partition AR pre-whiten algorithm in the sense of echo-to-reverberation ratio (ERR).
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There are many interpolation methods, among them, bilinear (BL) and bicubic (BC) are more popular. However, these methods suffer from low quality edge blurring and aliasing effect. In the other hand, if high resolution images are not... more
There are many interpolation methods, among them, bilinear (BL) and bicubic (BC) are more popular. However, these methods suffer from low quality edge blurring and aliasing effect. In the other hand, if high resolution images are not available, it is impossible to produce high quality display images and prints. To overcome this drawback, in this paper, we proposed a new
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This paper introduces a computer-assisted diagnosis (CAD) system for automatic mitosis detection from breast cancer histopathology slide images. In this system, a new approach for reducing the number of false positives is proposed based... more
This paper introduces a computer-assisted diagnosis (CAD) system for automatic mitosis detection from breast cancer histopathology slide images. In this system, a new approach for reducing the number of false positives is proposed based on Teaching-Learning-Based optimization (TLBO). The proposed CAD system is implemented on the histopathology slide images acquired by Aperio XT scanner (scanner A). In TLBO algorithm, the number of false positives (falsely detected nonmitosis candidates as mitosis ones) is defined as a cost function and, by minimizing it, many of nonmitosis candidates will be removed. Then some color and texture (textural) features such as those derived from cooccurrence and run-length matrices are extracted from the remaining candidates and finally mitotic cells are classified using a specific support vector machine (SVM) classifier. The simulation results have proven the claims about the high performance and efficiency of the proposed CAD system.
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Introduction: Demographic studies of a disease can reveal the characteristics of that disease among a specific population and will help the physicians to achieve a more accurate perception about it.The demographic of Lichen PlanoPilaris... more
Introduction: Demographic studies of a disease can reveal the characteristics of that disease among a specific population and will help the physicians to achieve a more accurate perception about it.The demographic of Lichen PlanoPilaris (LPP) among the Iranian population is unknown. The aim of this study is to describe the clinical, demographic, and histopathologic findings of lichen planopilaris in the Iranian population. Materials and Methods: In this cross-sectional study, all the patients with Lichen planopilaris were referred to the dermatology clinic of Imam Khomeini hospital from 2013 to 2015. Lichen planopilaris can be diagnosed by collecting histological evidence, dermatological examination, and clinical diagnosis. Their demographic characteristics, drug histories, onset of disease, and family histories were obtained by written questionnaire. Additionally, this study employed SPSS v.20 as the statistical analysis software. Results: One hundred patients were enrolled in this study. With an average age of 47.11 years, 78% of the patients were female, and 50 of these were housewives. The patients included were often from Tehran with Fars ethnicity. Among these patients, 7 had alopecia areata skin disease, and 10 of them suffered from thyroid disease. Most of the histopathology samples collected from these biopsies revealed degeneration of the basal layer of the follicular structure, perifollicular fibrosis, inflammatory cells, and atrophy of the pilosebaceous structures. Conclusion: Both the age spectrum and the disease distribution of LPP among the Iranian population were very diverse when compared to previous studies. Moreover, this study helps the physicians to have a brighter vision about the main reason and cause of LPP spread among diverse Iranian Ethnicities.