Behnam Kiani Kalejahi | University of Tabriz (original) (raw)

Papers by Behnam Kiani Kalejahi

Diagnostics

Images of brain tumors may only show up in a small subset of scans, so important details may be m... more Images of brain tumors may only show up in a small subset of scans, so important details may be missed. Further, because labeling is typically a labor-intensive and time-consuming task, there are typically only a small number of medical imaging datasets available for analysis. The focus of this research is on the MRI images of the human brain, and an attempt has been made to propose a method for the accurate segmentation of these images to identify the correct location of tumors. In this study, GAN is utilized as a classification network to detect and segment of 3D MRI images. The 3D GAN network model provides dense connectivity, followed by rapid network convergence and improved information extraction. Mutual training in a generative adversarial network can bring the segmentation results closer to the labeled data to improve image segmentation. The BraTS 2021 dataset of 3D images was used to compare two experimental models.

DOAJ (DOAJ: Directory of Open Access Journals), Nov 1, 2020

Blockchain technology is the first successful Bitcoin Network. It enables the ledger become more ... more Blockchain technology is the first successful Bitcoin Network. It enables the ledger become more decentralized and secure. Since it is not limited to bitcoin and controlled by third parties by government, corporations or banks, the technology is capturing the number of industries including cryptocurrency, infrastructure& hardware, financial technology, Internet&mobile ans so on. Blockchain is used as public ledger to verify all transactions of peer to peer system and to maintain traded bitcoin spending from central authorities while transactions have been distributed by Bitcoin. Achieving high blockchain-based performance and privacy & security are global issues that are desire to be overcome as claims show they are still significant challenges in many blockchain applications. Thus, this paper provides an introduction of Blockchain and the process of this technology in a way of outlining blockchain types. In addition, recent advances & challenges, real economy integration and current situations of this technology has been listed.

arXiv (Cornell University), Dec 26, 2019

text classification systems will help to solve the text clustering problem in the Azerbaijani lan... more text classification systems will help to solve the text clustering problem in the Azerbaijani language. There are some text-classification applications for foreign languages, but we tried to build a newly developed system to solve this problem for the Azerbaijani language. Firstly, we tried to find out potential practice areas. The system will be useful in a lot of areas. It will be mostly used in news feed categorization. News websites can automatically categorize news into classes such as sports, business, education, science, etc. The system is also used in sentiment analysis for product reviews. For example, the company shares a photo of a new product on Facebook and the company receives a thousand comments for new products. The systems classify the comments into categories like positive or negative. The system can also be applied in recommended systems, spam filtering, etc. Various machine learning techniques such as Naive Bayes, SVM, Decision Trees have been devised to solve the text classification problem in Azerbaijani language.

arXiv (Cornell University), Dec 15, 2019

Patient skeletal age estimation using a skeletal bone age assessment method is a time consuming a... more Patient skeletal age estimation using a skeletal bone age assessment method is a time consuming and very boring process. Today, in order to overcome these deficiencies, computerized techniques are used to replace hand-held techniques in the medical industry, to the extent that this results in the better evaluation. The purpose of this research is to minimize the problems of the division of existing systems with deep learning algorithms and the high accuracy of diagnosis. The evaluation of skeletal bone age is the most clinical application for the study of endocrinology, genetic disorders and growth in young people. This assessment is usually performed using the radiologic analysis of the left wrist using the GP(Greulich-Pyle) technique or the TW(Tanner-Whitehouse) technique. Both techniques have many disadvantages, including a lack of human deductions from observations as well as being time-consuming.

Signal, Image and Video Processing

One of the most critical problems in medical imaging is having high-quality data on healthy and s... more One of the most critical problems in medical imaging is having high-quality data on healthy and sick patients. Also, gathering and creating a useful dataset is very time-consuming and is not always cost-effective. Machine learning methods are the newest methods in image processing, especially in medical image processing for classification, segmentation, and translation. GAN (Generative Adversarial Networks) is a class of machine learning frameworks that we consider a solution to image-to-image translation problems and augmentation. One of GAN's applications is generating more realistic data for training and validation to improve the performance of the algorithm and evaluation. In this paper, we propose a high-quality image-to-image translation framework based on CycleGAN in a paired and unpaired model of translation from T1 (or T2) to T2 (or T1) weighted MRI (Magnetic Resonance Imaging) of brain images. For evaluation, we used a dataset that consisted of T1 and T2 images acquire...

Intelligent Data Analysis

Diagnosis of liver disease using computer-aided detection (CAD) systems is one of the most effici... more Diagnosis of liver disease using computer-aided detection (CAD) systems is one of the most efficient and cost-effective methods of medical image diagnosis. Accurate disease detection by using ultrasound images or other medical imaging modalities depends on the physician’s or doctor’s experience and skill. CAD systems have a critical role in helping experts make accurate and right-sized assessments. There are different types of CAD systems for diagnosing different diseases, and one of the applications is in liver disease diagnosis and detection by using intelligent algorithms to detect any abnormalities. Machine learning and deep learning algorithms and models play also a big role in this area. In this article, we tried to review the techniques which are utilized in different stages of CAD systems and pursue the methods used in preprocessing, extracting, and selecting features and classification. Also, different techniques are used to segment and analyze the liver ultrasound medical ...

Journal of Advances in Computer Engineering and Technology, Nov 1, 2020

Journal of Medical Signals & Sensors, 2021

Background: One of the common limitations in the treatment of cancer is in the early detection of... more Background: One of the common limitations in the treatment of cancer is in the early detection of this disease. The customary medical practice of cancer examination is a visual examination by the dermatologist followed by an invasive biopsy. Nonetheless, this symptomatic approach is time-consuming and prone to human errors. An automated machine learning model is essential to capacitate fast diagnoses and early treatment. Objective: The key objective of this study is to establish a fully automatic model that helps Dermatologists in skin cancer handling process in a way that could improve skin lesion classification accuracy. Method: The work is conducted following an implementation of a Deep Convolutional Generative Adversarial Network (DCGAN) using the Python-based deep learning library Keras. We incorporated effective image filtering and enhancement algorithms such as bilateral filter to enhance feature detection and extraction during training. The Deep Convolutional Generative Adversarial Network (DCGAN) needed slightly more fine-tuning to ripe a better return. Hyperparameter optimization was utilized for selecting the best-performed hyperparameter combinations and several network hyperparameters. In this work, we decreased the learning rate from the default 0.001 to 0.0002, and the momentum for Adam optimization algorithm from 0.9 to 0.5, in trying to reduce the instability issues related to GAN models and at each iteration the weights of the discriminative and generative network were updated to balance the loss between them. We endeavour to address a binary classification which predicts two classes present in our dataset, namely benign and malignant. More so, some well-known metrics such as the receiver operating characteristic -area under the curve and confusion matrix were incorporated for evaluating the results and classification accuracy. Results: The model generated very conceivable lesions during the early stages of the experiment and we could easily visualise a smooth transition in resolution along the way. Thus, we have achieved an overall test accuracy of 93.5% after fine-tuning most parameters of our network. Conclusion: This classification model provides spatial intelligence that could be useful in the future for cancer risk prediction. Unfortunately, it is difficult to generate high quality images that are much like the synthetic real samples and to compare different classification methods given the fact that some methods use non-public datasets for training.

The evidence says that liver disease detection using CAD is one of the most efficient techniques ... more The evidence says that liver disease detection using CAD is one of the most efficient techniques but the presence of better organization of studies and the performance parameters to represent the result analysis of the proposed techniques are pointedly missing in most of the recent studies. Few benchmarked studies have been found in some of the papers as benchmarking makes a reader understand that under which circumstances their experimental results or outcomes are better and useful for the future implementation and adoption of the work. Liver diseases and image processing algorithms, especially in medicine, are the most important and important topics of the day. Unfortunately, the necessary data and data, as they are invoked in the articles, are low in this area and require the revision and implementation of policies in order to gather and do more research in this field. Detection with ultrasound is quite normal in liver diseases and depends on the physician's experience and sk...

2020 28th Iranian Conference on Electrical Engineering (ICEE), 2020

Patient skeletal age estimation using a skeletal bone age assessment method is a time consuming a... more Patient skeletal age estimation using a skeletal bone age assessment method is a time consuming and very boring process. Today, in order to overcome these deficiencies, computerized techniques are used to replace hand-held techniques in the medical industry, to the extent that this results in better evaluation. The purpose of this research is to minimize the problems of the division of existing systems with deep learning algorithms and the high accuracy of diagnosis. The evaluation of skeletal bone age is the most clinical application for the study of endocrinology, genetic disorders and growth in young people. This assessment is usually performed using the radiologic analysis of the left wrist using the GP (Greulich-Pyle) technique or the TW(Tanner-Whitehouse) technique. Both techniques have many disadvantages, including a lack of human deductions from observations as well as being time-consuming.

This paper embodies the usage of Big Data in Healthcare. It is important to note that big data in... more This paper embodies the usage of Big Data in Healthcare. It is important to note that big data in terms of Architecture and implementation might be or has already or will continue to assist the continuous growth in the field of healthcare. The main important aspects of this study are the general importance of big data in healthcare, the positives big data will help tackle and enhance in this field and not to also forget to mention the tremendous downside big data has on healthcare that is still needed to improve or putting extensive research on. We believe there is still a long way in which institutions and individuals understand the hidden truth about big data. We have highlighted the various ways one could be confidently relied on big data and on the other hand highlighted the weighted importance of big problem big data and expected solutions.

In the era of technology, data security is one of the most important things that both individuals... more In the era of technology, data security is one of the most important things that both individuals and companies need. Information plays a huge role in our everyday life and keeping it safe should be our number one priority. Nowadays most of the information is transferred via the internet. One of the ways to use it is telemedicine. With the help of telemedicine, people can have an appointment at the doctors without losing their time or money. All of the information about one's health is transferred through the internet but is it that safe? What techniques are used to provide the safety of our confidential information? To guarantee that the information is not changed or that in case it will be stolen no one can still have access to it.

Wireless Personal Communications

In the century of automation, which is digitized, and more and more technology is used, automatic... more In the century of automation, which is digitized, and more and more technology is used, automatic systems' replacement of old manual systems makes people's lives easier. Nowadays, people have made the Internet an integral part of humans' daily lives unless they are insecure. The Internet of Things (IoT) secures a platform that authorizes devices and sensors to be remotely detected, connected, and controlled over the Internet. Due to the developments in sensor technologies, the production of tiny and low-cost sensors has increased. Many sensors, such as temperature, pressure, vibration, sound, light, can be used in the IoT. As a result of the development of these sensors with new generations, the power of the IoT technology increases, and accordingly, the revolution of IoT applications are developing rapidly. Therefore, their security issues and threats are challenging topics. In this paper, the benefits and open issues, threats, limitations of IoT applications are presented. The assessment shows that the most influential factor for evaluating IoT applications is the cost that is used in 79% of all articles, then the real-time-ness that is used in 64%, and security and error are used in 57% of all reviewed articles.

International Journal of Communication Systems

Computer Systems Science and Engineering

Text classification systems will help to solve the text clustering problem in the Azerbaijani lan... more Text classification systems will help to solve the text clustering problem in the Azerbaijani language. There are some text-classification applications for foreign languages, but we tried to build a newly developed system to solve this problem for the Azerbaijani language. Firstly, we tried to find out potential practice areas. The system will be useful in a lot of areas. It will be mostly used in news feed categorization. News websites can automatically categorize news into classes such as sports, business, education, science, etc. The system is also used in sentiment analysis for product reviews. For example, the company shares a photo of a new product on Facebook and the company receives a thousand comments for new products. The systems classify comments like positive or negative. The system can also be applied in recommended systems, spam filtering, etc. Various machine learning techniques such as Naive Bayes, SVM, Multi-layer Perceptron have been devised to solve the text classification problem in Azerbaijani language.

Diagnostics

Images of brain tumors may only show up in a small subset of scans, so important details may be m... more Images of brain tumors may only show up in a small subset of scans, so important details may be missed. Further, because labeling is typically a labor-intensive and time-consuming task, there are typically only a small number of medical imaging datasets available for analysis. The focus of this research is on the MRI images of the human brain, and an attempt has been made to propose a method for the accurate segmentation of these images to identify the correct location of tumors. In this study, GAN is utilized as a classification network to detect and segment of 3D MRI images. The 3D GAN network model provides dense connectivity, followed by rapid network convergence and improved information extraction. Mutual training in a generative adversarial network can bring the segmentation results closer to the labeled data to improve image segmentation. The BraTS 2021 dataset of 3D images was used to compare two experimental models.

DOAJ (DOAJ: Directory of Open Access Journals), Nov 1, 2020

Blockchain technology is the first successful Bitcoin Network. It enables the ledger become more ... more Blockchain technology is the first successful Bitcoin Network. It enables the ledger become more decentralized and secure. Since it is not limited to bitcoin and controlled by third parties by government, corporations or banks, the technology is capturing the number of industries including cryptocurrency, infrastructure& hardware, financial technology, Internet&mobile ans so on. Blockchain is used as public ledger to verify all transactions of peer to peer system and to maintain traded bitcoin spending from central authorities while transactions have been distributed by Bitcoin. Achieving high blockchain-based performance and privacy & security are global issues that are desire to be overcome as claims show they are still significant challenges in many blockchain applications. Thus, this paper provides an introduction of Blockchain and the process of this technology in a way of outlining blockchain types. In addition, recent advances & challenges, real economy integration and current situations of this technology has been listed.

arXiv (Cornell University), Dec 26, 2019

text classification systems will help to solve the text clustering problem in the Azerbaijani lan... more text classification systems will help to solve the text clustering problem in the Azerbaijani language. There are some text-classification applications for foreign languages, but we tried to build a newly developed system to solve this problem for the Azerbaijani language. Firstly, we tried to find out potential practice areas. The system will be useful in a lot of areas. It will be mostly used in news feed categorization. News websites can automatically categorize news into classes such as sports, business, education, science, etc. The system is also used in sentiment analysis for product reviews. For example, the company shares a photo of a new product on Facebook and the company receives a thousand comments for new products. The systems classify the comments into categories like positive or negative. The system can also be applied in recommended systems, spam filtering, etc. Various machine learning techniques such as Naive Bayes, SVM, Decision Trees have been devised to solve the text classification problem in Azerbaijani language.

arXiv (Cornell University), Dec 15, 2019

Patient skeletal age estimation using a skeletal bone age assessment method is a time consuming a... more Patient skeletal age estimation using a skeletal bone age assessment method is a time consuming and very boring process. Today, in order to overcome these deficiencies, computerized techniques are used to replace hand-held techniques in the medical industry, to the extent that this results in the better evaluation. The purpose of this research is to minimize the problems of the division of existing systems with deep learning algorithms and the high accuracy of diagnosis. The evaluation of skeletal bone age is the most clinical application for the study of endocrinology, genetic disorders and growth in young people. This assessment is usually performed using the radiologic analysis of the left wrist using the GP(Greulich-Pyle) technique or the TW(Tanner-Whitehouse) technique. Both techniques have many disadvantages, including a lack of human deductions from observations as well as being time-consuming.

Signal, Image and Video Processing

One of the most critical problems in medical imaging is having high-quality data on healthy and s... more One of the most critical problems in medical imaging is having high-quality data on healthy and sick patients. Also, gathering and creating a useful dataset is very time-consuming and is not always cost-effective. Machine learning methods are the newest methods in image processing, especially in medical image processing for classification, segmentation, and translation. GAN (Generative Adversarial Networks) is a class of machine learning frameworks that we consider a solution to image-to-image translation problems and augmentation. One of GAN's applications is generating more realistic data for training and validation to improve the performance of the algorithm and evaluation. In this paper, we propose a high-quality image-to-image translation framework based on CycleGAN in a paired and unpaired model of translation from T1 (or T2) to T2 (or T1) weighted MRI (Magnetic Resonance Imaging) of brain images. For evaluation, we used a dataset that consisted of T1 and T2 images acquire...

Intelligent Data Analysis

Diagnosis of liver disease using computer-aided detection (CAD) systems is one of the most effici... more Diagnosis of liver disease using computer-aided detection (CAD) systems is one of the most efficient and cost-effective methods of medical image diagnosis. Accurate disease detection by using ultrasound images or other medical imaging modalities depends on the physician’s or doctor’s experience and skill. CAD systems have a critical role in helping experts make accurate and right-sized assessments. There are different types of CAD systems for diagnosing different diseases, and one of the applications is in liver disease diagnosis and detection by using intelligent algorithms to detect any abnormalities. Machine learning and deep learning algorithms and models play also a big role in this area. In this article, we tried to review the techniques which are utilized in different stages of CAD systems and pursue the methods used in preprocessing, extracting, and selecting features and classification. Also, different techniques are used to segment and analyze the liver ultrasound medical ...

Journal of Advances in Computer Engineering and Technology, Nov 1, 2020

Journal of Medical Signals & Sensors, 2021

Background: One of the common limitations in the treatment of cancer is in the early detection of... more Background: One of the common limitations in the treatment of cancer is in the early detection of this disease. The customary medical practice of cancer examination is a visual examination by the dermatologist followed by an invasive biopsy. Nonetheless, this symptomatic approach is time-consuming and prone to human errors. An automated machine learning model is essential to capacitate fast diagnoses and early treatment. Objective: The key objective of this study is to establish a fully automatic model that helps Dermatologists in skin cancer handling process in a way that could improve skin lesion classification accuracy. Method: The work is conducted following an implementation of a Deep Convolutional Generative Adversarial Network (DCGAN) using the Python-based deep learning library Keras. We incorporated effective image filtering and enhancement algorithms such as bilateral filter to enhance feature detection and extraction during training. The Deep Convolutional Generative Adversarial Network (DCGAN) needed slightly more fine-tuning to ripe a better return. Hyperparameter optimization was utilized for selecting the best-performed hyperparameter combinations and several network hyperparameters. In this work, we decreased the learning rate from the default 0.001 to 0.0002, and the momentum for Adam optimization algorithm from 0.9 to 0.5, in trying to reduce the instability issues related to GAN models and at each iteration the weights of the discriminative and generative network were updated to balance the loss between them. We endeavour to address a binary classification which predicts two classes present in our dataset, namely benign and malignant. More so, some well-known metrics such as the receiver operating characteristic -area under the curve and confusion matrix were incorporated for evaluating the results and classification accuracy. Results: The model generated very conceivable lesions during the early stages of the experiment and we could easily visualise a smooth transition in resolution along the way. Thus, we have achieved an overall test accuracy of 93.5% after fine-tuning most parameters of our network. Conclusion: This classification model provides spatial intelligence that could be useful in the future for cancer risk prediction. Unfortunately, it is difficult to generate high quality images that are much like the synthetic real samples and to compare different classification methods given the fact that some methods use non-public datasets for training.

The evidence says that liver disease detection using CAD is one of the most efficient techniques ... more The evidence says that liver disease detection using CAD is one of the most efficient techniques but the presence of better organization of studies and the performance parameters to represent the result analysis of the proposed techniques are pointedly missing in most of the recent studies. Few benchmarked studies have been found in some of the papers as benchmarking makes a reader understand that under which circumstances their experimental results or outcomes are better and useful for the future implementation and adoption of the work. Liver diseases and image processing algorithms, especially in medicine, are the most important and important topics of the day. Unfortunately, the necessary data and data, as they are invoked in the articles, are low in this area and require the revision and implementation of policies in order to gather and do more research in this field. Detection with ultrasound is quite normal in liver diseases and depends on the physician's experience and sk...

2020 28th Iranian Conference on Electrical Engineering (ICEE), 2020

Patient skeletal age estimation using a skeletal bone age assessment method is a time consuming a... more Patient skeletal age estimation using a skeletal bone age assessment method is a time consuming and very boring process. Today, in order to overcome these deficiencies, computerized techniques are used to replace hand-held techniques in the medical industry, to the extent that this results in better evaluation. The purpose of this research is to minimize the problems of the division of existing systems with deep learning algorithms and the high accuracy of diagnosis. The evaluation of skeletal bone age is the most clinical application for the study of endocrinology, genetic disorders and growth in young people. This assessment is usually performed using the radiologic analysis of the left wrist using the GP (Greulich-Pyle) technique or the TW(Tanner-Whitehouse) technique. Both techniques have many disadvantages, including a lack of human deductions from observations as well as being time-consuming.

This paper embodies the usage of Big Data in Healthcare. It is important to note that big data in... more This paper embodies the usage of Big Data in Healthcare. It is important to note that big data in terms of Architecture and implementation might be or has already or will continue to assist the continuous growth in the field of healthcare. The main important aspects of this study are the general importance of big data in healthcare, the positives big data will help tackle and enhance in this field and not to also forget to mention the tremendous downside big data has on healthcare that is still needed to improve or putting extensive research on. We believe there is still a long way in which institutions and individuals understand the hidden truth about big data. We have highlighted the various ways one could be confidently relied on big data and on the other hand highlighted the weighted importance of big problem big data and expected solutions.

In the era of technology, data security is one of the most important things that both individuals... more In the era of technology, data security is one of the most important things that both individuals and companies need. Information plays a huge role in our everyday life and keeping it safe should be our number one priority. Nowadays most of the information is transferred via the internet. One of the ways to use it is telemedicine. With the help of telemedicine, people can have an appointment at the doctors without losing their time or money. All of the information about one's health is transferred through the internet but is it that safe? What techniques are used to provide the safety of our confidential information? To guarantee that the information is not changed or that in case it will be stolen no one can still have access to it.

Wireless Personal Communications

In the century of automation, which is digitized, and more and more technology is used, automatic... more In the century of automation, which is digitized, and more and more technology is used, automatic systems' replacement of old manual systems makes people's lives easier. Nowadays, people have made the Internet an integral part of humans' daily lives unless they are insecure. The Internet of Things (IoT) secures a platform that authorizes devices and sensors to be remotely detected, connected, and controlled over the Internet. Due to the developments in sensor technologies, the production of tiny and low-cost sensors has increased. Many sensors, such as temperature, pressure, vibration, sound, light, can be used in the IoT. As a result of the development of these sensors with new generations, the power of the IoT technology increases, and accordingly, the revolution of IoT applications are developing rapidly. Therefore, their security issues and threats are challenging topics. In this paper, the benefits and open issues, threats, limitations of IoT applications are presented. The assessment shows that the most influential factor for evaluating IoT applications is the cost that is used in 79% of all articles, then the real-time-ness that is used in 64%, and security and error are used in 57% of all reviewed articles.

International Journal of Communication Systems

Computer Systems Science and Engineering

Text classification systems will help to solve the text clustering problem in the Azerbaijani lan... more Text classification systems will help to solve the text clustering problem in the Azerbaijani language. There are some text-classification applications for foreign languages, but we tried to build a newly developed system to solve this problem for the Azerbaijani language. Firstly, we tried to find out potential practice areas. The system will be useful in a lot of areas. It will be mostly used in news feed categorization. News websites can automatically categorize news into classes such as sports, business, education, science, etc. The system is also used in sentiment analysis for product reviews. For example, the company shares a photo of a new product on Facebook and the company receives a thousand comments for new products. The systems classify comments like positive or negative. The system can also be applied in recommended systems, spam filtering, etc. Various machine learning techniques such as Naive Bayes, SVM, Multi-layer Perceptron have been devised to solve the text classification problem in Azerbaijani language.