In this paper, we propose a technique to locate abnormal growth of cells in breast tissue and suggest further pathological test, when require. We compare normal breast tissue with malignant invasive breast tissue by a...In this paper, we propose a technique to locate abnormal growth of cells in breast tissue and suggest further pathological test, when require. We compare normal breast tissue with malignant invasive breast tissue by a series of image processing steps. Normal ductal epithelial cells and ductal/lobular invasive carcinogenic cells also consider for comparison here in this paper. In fact, features of cancerous breast tissue （invasive） are extracted and analyses with normal breast tissue. We also suggest the breast cancer recognition technique through image processing and prevention by controlling p53 gene mutation to some extent.展开更多
Lung cancer is the leading cause of mortality in the world affectingboth men and women equally.When a radiologist just focuses on the patient’sbody, it increases the amount of strain on the radiologist and the likeli...Lung cancer is the leading cause of mortality in the world affectingboth men and women equally.When a radiologist just focuses on the patient’sbody, it increases the amount of strain on the radiologist and the likelihoodof missing pathological information such as abnormalities are increased.One of the primary objectives of this research work is to develop computerassisteddiagnosis and detection of lung cancer. It also intends to make iteasier for radiologists to identify and diagnose lung cancer accurately. Theproposed strategy which was based on a unique image feature, took intoconsideration the spatial interaction of voxels that were next to one another.Using the U-NET+Three parameter logistic distribution-based technique, wewere able to replicate the situation. The proposed technique had an averageDice co-efficient (DSC) of 97.3%, a sensitivity of 96.5% and a specificity of94.1% when tested on the Luna-16 dataset. This research investigates howdiverse lung segmentation, juxta pleural nodule inclusion, and pulmonarynodule segmentation approaches may be applied to create Computer AidedDiagnosis (CAD) systems. When we compared our approach to four otherlung segmentation methods, we discovered that ours was the most successful.We employed 40 patients from Luna-16 datasets to evaluate this. In termsof DSC performance, the findings demonstrate that the suggested techniqueoutperforms the other strategies by a significant margin.展开更多
In Wireless Sensor Network(WSN),coverage and connectivity are the vital challenges in the target-based region.The linear objective is to find the positions to cover the complete target nodes and connectivity between e...In Wireless Sensor Network(WSN),coverage and connectivity are the vital challenges in the target-based region.The linear objective is to find the positions to cover the complete target nodes and connectivity between each sensor for data forwarding towards the base station given a grid with target points and a potential sensor placement position.In this paper,a multiobjective problem on target-based WSN(t-WSN)is derived,which minimizes the number of deployed nodes,and maximizes the cost of coverage and sensing range.An Evolutionary-based Non-Dominated Sorting Genetic Algorithm-II(NSGA-II)is incorporated to tackle this multiobjective problem efficiently.Multiobjective problems are intended to solve different objectives of a problem simultaneously.Bio-inspired algorithms address the NP-hard problem most effectively in recent years.In NSGA-II,the Non-Dominated sorting preserves the better solution in different objectives simultaneously using dominance relation.In the diversity maintenance phase,density estimation and crowd comparison are the two components that balance the exploration and exploitation phase of the algorithm.Performance of NSGA-II on this multiobjective problem is evaluated in terms of performance indicators Overall Non-dominated Vector Generation(ONGV)and Spacing(SP).The simulation results show the proposed method performs outperforms the existing algorithms in different aspects of the model.展开更多
In this paper a novel technique, Authentication and Secret Message Transmission using Discrete Fourier Transformation (ASMTDFT) has been proposed to authenticate an image and also some secret message or image can be t...In this paper a novel technique, Authentication and Secret Message Transmission using Discrete Fourier Transformation (ASMTDFT) has been proposed to authenticate an image and also some secret message or image can be transmitted over the network. Instead of direct embedding a message or image within the source image, choosing a window of size 2 x 2 of the source image in sliding window manner and then con-vert it from spatial domain to frequency domain using Discrete Fourier Transform (DFT). The bits of the authenticating message or image are then embedded at LSB within the real part of the transformed image. Inverse DFT is performed for the transformation from frequency domain to spatial domain as final step of encoding. Decoding is done through the reverse procedure. The experimental results have been discussed and compared with the existing steganography algorithm S-Tools. Histogram analysis and Chi-Square test of source image with embedded image shows the better results in comparison with the S-Tools.展开更多
This paper propose a computerized method of magnetic resonance imaging （MR/） of brain binarization for the uses of preprocessing of features extraction and brain ab- normality identification. One of the main problem...This paper propose a computerized method of magnetic resonance imaging （MR/） of brain binarization for the uses of preprocessing of features extraction and brain ab- normality identification. One of the main problems of MR/ binarization is that many pixels of brain part cannot be cor- rectly binarized due to extensive black background or large variation in contrast between background and foreground of MR/. We have proposed a binarization that uses mean, vari- ance, standard deviation and entropy to determine a thresh- old value followed by a non-gamut enhancement which can overcome the binarization problem of brain component. The proposed binarization technique is extensively tested with a variety of MR/and generates good binarization with im- proved accuracy and reduced error. A comparison is carried out among the obtained outcome with this innovative method with respect to other well-known methods.展开更多
文摘In this paper, we propose a technique to locate abnormal growth of cells in breast tissue and suggest further pathological test, when require. We compare normal breast tissue with malignant invasive breast tissue by a series of image processing steps. Normal ductal epithelial cells and ductal/lobular invasive carcinogenic cells also consider for comparison here in this paper. In fact, features of cancerous breast tissue （invasive） are extracted and analyses with normal breast tissue. We also suggest the breast cancer recognition technique through image processing and prevention by controlling p53 gene mutation to some extent.
基金supported by the Ministry of SMEs and Startups (MSS),Korea,under the“Startup growth technology development program (R&D,S3125114)”by the Ministry of Small and Medium-sized Enterprises (SMEs)and Startups (MSS),Korea,under the“Regional Specialized Industry Development Plus Program (R&D,S3246057)”supervised by the Korea Institute for Advancement of Technology (KIAT).
文摘Lung cancer is the leading cause of mortality in the world affectingboth men and women equally.When a radiologist just focuses on the patient’sbody, it increases the amount of strain on the radiologist and the likelihoodof missing pathological information such as abnormalities are increased.One of the primary objectives of this research work is to develop computerassisteddiagnosis and detection of lung cancer. It also intends to make iteasier for radiologists to identify and diagnose lung cancer accurately. Theproposed strategy which was based on a unique image feature, took intoconsideration the spatial interaction of voxels that were next to one another.Using the U-NET+Three parameter logistic distribution-based technique, wewere able to replicate the situation. The proposed technique had an averageDice co-efficient (DSC) of 97.3%, a sensitivity of 96.5% and a specificity of94.1% when tested on the Luna-16 dataset. This research investigates howdiverse lung segmentation, juxta pleural nodule inclusion, and pulmonarynodule segmentation approaches may be applied to create Computer AidedDiagnosis (CAD) systems. When we compared our approach to four otherlung segmentation methods, we discovered that ours was the most successful.We employed 40 patients from Luna-16 datasets to evaluate this. In termsof DSC performance, the findings demonstrate that the suggested techniqueoutperforms the other strategies by a significant margin.
基金This research has been funded with the support of the project SP2021/45,assigned to VSB-Technical University of Ostrava,the Ministry of Education,Youth and Sports in the Czech Republic.
文摘In Wireless Sensor Network(WSN),coverage and connectivity are the vital challenges in the target-based region.The linear objective is to find the positions to cover the complete target nodes and connectivity between each sensor for data forwarding towards the base station given a grid with target points and a potential sensor placement position.In this paper,a multiobjective problem on target-based WSN(t-WSN)is derived,which minimizes the number of deployed nodes,and maximizes the cost of coverage and sensing range.An Evolutionary-based Non-Dominated Sorting Genetic Algorithm-II(NSGA-II)is incorporated to tackle this multiobjective problem efficiently.Multiobjective problems are intended to solve different objectives of a problem simultaneously.Bio-inspired algorithms address the NP-hard problem most effectively in recent years.In NSGA-II,the Non-Dominated sorting preserves the better solution in different objectives simultaneously using dominance relation.In the diversity maintenance phase,density estimation and crowd comparison are the two components that balance the exploration and exploitation phase of the algorithm.Performance of NSGA-II on this multiobjective problem is evaluated in terms of performance indicators Overall Non-dominated Vector Generation(ONGV)and Spacing(SP).The simulation results show the proposed method performs outperforms the existing algorithms in different aspects of the model.
文摘In this paper a novel technique, Authentication and Secret Message Transmission using Discrete Fourier Transformation (ASMTDFT) has been proposed to authenticate an image and also some secret message or image can be transmitted over the network. Instead of direct embedding a message or image within the source image, choosing a window of size 2 x 2 of the source image in sliding window manner and then con-vert it from spatial domain to frequency domain using Discrete Fourier Transform (DFT). The bits of the authenticating message or image are then embedded at LSB within the real part of the transformed image. Inverse DFT is performed for the transformation from frequency domain to spatial domain as final step of encoding. Decoding is done through the reverse procedure. The experimental results have been discussed and compared with the existing steganography algorithm S-Tools. Histogram analysis and Chi-Square test of source image with embedded image shows the better results in comparison with the S-Tools.
文摘This paper propose a computerized method of magnetic resonance imaging （MR/） of brain binarization for the uses of preprocessing of features extraction and brain ab- normality identification. One of the main problems of MR/ binarization is that many pixels of brain part cannot be cor- rectly binarized due to extensive black background or large variation in contrast between background and foreground of MR/. We have proposed a binarization that uses mean, vari- ance, standard deviation and entropy to determine a thresh- old value followed by a non-gamut enhancement which can overcome the binarization problem of brain component. The proposed binarization technique is extensively tested with a variety of MR/and generates good binarization with im- proved accuracy and reduced error. A comparison is carried out among the obtained outcome with this innovative method with respect to other well-known methods.
