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The International Journal on the Image最新文献

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Toward a deep augmented reality medical images diagnosis generation 面向深度增强现实医学图像诊断生成
The International Journal on the Image Pub Date : 2021-06-16 DOI: 10.1504/IJIM.2021.10038412
Sabrine Benzarti, W. Karaa, H. Ghézala
{"title":"Toward a deep augmented reality medical images diagnosis generation","authors":"Sabrine Benzarti, W. Karaa, H. Ghézala","doi":"10.1504/IJIM.2021.10038412","DOIUrl":"https://doi.org/10.1504/IJIM.2021.10038412","url":null,"abstract":"Augmented reality (AR) and deep learning (DL) are promising areas. In this paper, we present the impact of such assortment (AR/DL) on the enhancement of generating textual and oral descriptions from a target medical image. The main purpose is to assist medical practitioners to make an accurate decision about a generated diagnosis. Automatic medical image report generation (textual and vocal) is used up as a diagnostic aid system for disease diagnoses depend strongly on visual properties. In this paper, we will describe how we develop an augmented report for the X-ray image target. Primary results using prototypes are promising. Doctors, learner's task are more efficient and feedbacks are encouraging.","PeriodicalId":433219,"journal":{"name":"The International Journal on the Image","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116860059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Vehicle detection in wide-area aerial imagery: cross-association of detection schemes with post-processings 广域航空图像中的车辆检测:检测方案与后处理的交叉关联
The International Journal on the Image Pub Date : 2018-11-30 DOI: 10.1504/IJIM.2018.10017603
Xin Gao
{"title":"Vehicle detection in wide-area aerial imagery: cross-association of detection schemes with post-processings","authors":"Xin Gao","doi":"10.1504/IJIM.2018.10017603","DOIUrl":"https://doi.org/10.1504/IJIM.2018.10017603","url":null,"abstract":"Post-processing schemes are crucial for object detection algorithms to improve the performance of detection in wide-area aerial imagery. We select appropriate parameters for three algorithms (variational minimax optimisation (Saha and Ray, 2009), feature density estimation (Gleason et al., 2011) and Zheng's scheme by morphological filtering (Zheng et al., 2013)) to achieve the highest average F-score on random sample frames, and then follow the same procedure to implement five post-processing schemes on each algorithm. Two low-resolution aerial videos are used as our datasets to compare automatic detection results with the ground truth objects on each frame. The performance analysis of post-processing schemes on each algorithm are presented under two sets of evaluation metrics.","PeriodicalId":433219,"journal":{"name":"The International Journal on the Image","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116631162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Hardware implementation of stereo vision algorithms for depth estimation 立体视觉深度估计算法的硬件实现
The International Journal on the Image Pub Date : 2018-11-30 DOI: 10.1504/IJIM.2018.10017594
Nitish J. Wadne, Arti V. Bang
{"title":"Hardware implementation of stereo vision algorithms for depth estimation","authors":"Nitish J. Wadne, Arti V. Bang","doi":"10.1504/IJIM.2018.10017594","DOIUrl":"https://doi.org/10.1504/IJIM.2018.10017594","url":null,"abstract":"Depth estimation has applications like robot navigation, advance driver assistance systems, 3D movies etc. Depth is represented in terms of disparity map which can be generated using various stereo correspondence algorithms. This paper presents an implementation of semi global block matching algorithm on raspberry pi to estimate the depth from the camera. The algorithm computes the disparity using block wise matching and smoothness constraint. The proposed algorithm is compared with SAD algorithm on personal computer as well as on raspberry pi. The algorithm is also further, evaluated on the standard dataset. The project aim is to detect people in an image and estimate their depth from the camera. The real time implementation of the proposed algorithm uses block size of 21 × 21 for images which has resolution of 1280 × 720 P. The algorithm estimates depth with an accuracy of 95%. The system also provides faster processing time to the proposed algorithm.","PeriodicalId":433219,"journal":{"name":"The International Journal on the Image","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128657824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A promising method for early detection of ischemic stroke area on brain CT images 一种有前途的脑CT图像早期检测缺血性脑卒中区域的方法
The International Journal on the Image Pub Date : 2018-11-30 DOI: 10.1504/IJIM.2018.10017604
Yahiaoui Amina Fatima Zahra, Bessaid Abdelhafid
{"title":"A promising method for early detection of ischemic stroke area on brain CT images","authors":"Yahiaoui Amina Fatima Zahra, Bessaid Abdelhafid","doi":"10.1504/IJIM.2018.10017604","DOIUrl":"https://doi.org/10.1504/IJIM.2018.10017604","url":null,"abstract":"Non-contrast computed tomography (NCCT) has been chosen as the modality of choice for stroke imaging due to its low price and high availability. However, subtle changes of ischemia are hard to visualise and to extract. Alberta Stroke Program Early CT Score (ASPECTS) has been developed to help radiologists to make decisions regarding thrombolytic treatment. Only patients with favourable baseline scans (8-10) benefitted from endovascular revascularisation therapy. The purpose of this study was to develop a novel approach for automated detection of ischemic stroke area on brain CT images within earliest hours after onset symptoms using comparison of brain hemispheres. Our algorithm has five steps: preprocessing, segmentation of Regions of Interest, elimination of old infarcts and cerebrospinal fluid (CSF) space, feature extraction and ASPECTS scoring. The method was applied to 25 patients who presented to LA MEKERRA imaging centre. Its gives an effective results comparing with literature and a high sensitivity 90.8%.","PeriodicalId":433219,"journal":{"name":"The International Journal on the Image","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129687896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Decision based fuzzy logic approach for multimodal medical image fusion in NSCT domain 基于决策的模糊逻辑NSCT多模态医学图像融合方法
The International Journal on the Image Pub Date : 2018-11-30 DOI: 10.1504/IJIM.2018.10016941
S. Sivasangumani
{"title":"Decision based fuzzy logic approach for multimodal medical image fusion in NSCT domain","authors":"S. Sivasangumani","doi":"10.1504/IJIM.2018.10016941","DOIUrl":"https://doi.org/10.1504/IJIM.2018.10016941","url":null,"abstract":"Image fusion is used to reduce the redundancy and increases the needed information in the processed image from two or more input images that have different information generated by different sources. The output image has more information and is more suitable for visual perception or processing tasks like medical imaging, remote sensing, concealed weapon detection, weather forecasting, biometrics etc. Image fusion methods basically accept only registered images to produce a high quality fused single image with spatial and spectral information. The fused image with more information will improve the performance of image analysis algorithms used in medical applications. In this paper, we proposed an image fusion algorithm based on decision approach and NSCT to improve the future resolution of the images. In this, images will be segmented into regions and decomposed into sub-images and then processed using Fuzzy Logic, the information fusion is performed using these images under the certain criteria such as non subsampled contourlet transform (NSCT) and certain fusion rules such as Fuzzy Logic, and finally these sub-images are reconstructed into the resultant image with plentiful information. The various metrices entropy, mutual information (MI) and Fusion Quality are calculated to compare the results. The proposed method is compared both subjectively as well as objectively with the other image fusion methods. The experimental results show that the proposed method is better than other fusion methods and increases the quality and PSNR of fused image.","PeriodicalId":433219,"journal":{"name":"The International Journal on the Image","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121490430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Comparative study of different machine learning classifiers for mammograms and brain MRI images 不同机器学习分类器对乳房x光片和脑MRI图像的比较研究
The International Journal on the Image Pub Date : 2018-11-30 DOI: 10.1504/IJIM.2018.10017591
Poonam Sonar, U. Bhosle, Chandrajit Choudhury
{"title":"Comparative study of different machine learning classifiers for mammograms and brain MRI images","authors":"Poonam Sonar, U. Bhosle, Chandrajit Choudhury","doi":"10.1504/IJIM.2018.10017591","DOIUrl":"https://doi.org/10.1504/IJIM.2018.10017591","url":null,"abstract":"Today, breast cancer in women has become the leading cause of cancer deaths. Mammography has been the most reliable and accurate technique for early and accurate detection of breast cancer. This paper presents machine learning based mammogram classification techniques. The authors propose an improved hybrid KNN-SVM classifier to improve the performance of the expert system. It is based on mapping feature points to kernel space and finds the K nearest neighbours for a given test data point among the training dataset. This narrow down search for support vectors to the more relevant data points. The proposed algorithm is tested on standard MIAS and DDSM mammograms databases and brain MRI database. The results are compared with different machine learning classifiers such as SVM, KNN, Random Forest, C4.5, Logistic Regression, Fisher Discriminant analysis, Naive Bayesian classifiers. The results show that the performance of the proposed classifier is better compared to the other classifiers.","PeriodicalId":433219,"journal":{"name":"The International Journal on the Image","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127204585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Trigonometry-based motion blur parameter estimation algorithm 基于三角函数的运动模糊参数估计算法
The International Journal on the Image Pub Date : 2018-07-06 DOI: 10.1504/IJIM.2018.10014060
Ruchi Gajjar, T. Zaveri, A. Banerjee, K. Murthy
{"title":"Trigonometry-based motion blur parameter estimation algorithm","authors":"Ruchi Gajjar, T. Zaveri, A. Banerjee, K. Murthy","doi":"10.1504/IJIM.2018.10014060","DOIUrl":"https://doi.org/10.1504/IJIM.2018.10014060","url":null,"abstract":"Restoration of blurred images requires information about the blurring function, which is generally unknown in practical applications. Identification of blur parameters is essential for yielding blurring function. This paper proposes a technique for estimation of motion blur parameters by formulating trigonometric relationship between the spectral lines of the motion blurred image and the blur parameters. In majority of the existing motion blur parameter estimation approaches, length of motion blur is estimated by rotating the Fourier spectrum to estimated motion angle. This requires angle estimation to be done forehand. The proposed method estimates both, length and angle simultaneously by exploring the trigonometric relation between spectral lines, thereby eliminating the need of spectrum rotation for length estimation. The proposed technique is applied on Berkeley segmentation dataset, Pascal VOC 2007 and USC-SIPI image database. The simulation results prove that the proposed method exhibit better parameter estimation performance as compared to existing state-of-the-art techniques.","PeriodicalId":433219,"journal":{"name":"The International Journal on the Image","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130981538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A novel method for query based image retrieval using prototype based clustering 基于原型聚类的基于查询的图像检索新方法
The International Journal on the Image Pub Date : 2018-07-06 DOI: 10.1504/IJIM.2018.10014064
R. Tamilkodi, G. Kumari, S. Maruthuperumal
{"title":"A novel method for query based image retrieval using prototype based clustering","authors":"R. Tamilkodi, G. Kumari, S. Maruthuperumal","doi":"10.1504/IJIM.2018.10014064","DOIUrl":"https://doi.org/10.1504/IJIM.2018.10014064","url":null,"abstract":"Content-based image retrieval is a process applied for searching of images from a large database in which searching is done based on the content of the image. The content of the image can be of colour, texture, and shape. This paper concentrates the primitive feature of texture in which the extraction of image content is considered. The implementation of such a system requires the extraction and storing of the image features to be compared with the features of the query image with this flow, the implementation process is more dynamic since all features have already been stored somewhere. This paper proposed a new method called prototype based cluster (PBC) where the features with similar values or properties are grouped together to form clusters and comparison is made between these clusters with the database images and the relevant images are retrieved and stored. This method will show good performance when compared with existing ones. The experimental result shows the effectiveness of our proposed method PBC applied on the query image.","PeriodicalId":433219,"journal":{"name":"The International Journal on the Image","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122560598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Generating efficient classifiers using facial components for age classification 使用面部成分生成有效的分类器进行年龄分类
The International Journal on the Image Pub Date : 2018-07-06 DOI: 10.1504/IJIM.2018.10014062
Sreejit Panicker, Smita Selot, Manisha Sharma
{"title":"Generating efficient classifiers using facial components for age classification","authors":"Sreejit Panicker, Smita Selot, Manisha Sharma","doi":"10.1504/IJIM.2018.10014062","DOIUrl":"https://doi.org/10.1504/IJIM.2018.10014062","url":null,"abstract":"Ageing a natural phenomenon, happens with time and becomes evident as a person grows. An individual undergoes various changes as age progresses. This is noticeable by his or her facial structure and texture which changes as growth accelerate. Facial growing is a standard happening that is sure, and differs from individual to individual subject on the conditions and living susceptibility. Uses of age assertion are seen in areas like Forensic science, security, and furthermore to decide wellbeing of an individual. Facial parameters used for age characterisation can be either structural or textural. In this paper, we have used statistical methodologies for feature extraction. In structural, facial development is considered for characterisation, by figuring the Euclidean separation between the different points of interest on the facial image. The experimental results are significant and remarkable.","PeriodicalId":433219,"journal":{"name":"The International Journal on the Image","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121932573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Analysis of diverse optimisation algorithms in breast cancer detection 多种优化算法在乳腺癌检测中的应用分析
The International Journal on the Image Pub Date : 2018-07-06 DOI: 10.1504/IJIM.2018.10014061
K. S. Kumar, K. Venkatalakshmi, K. Karthikeyan, A. Jabeen
{"title":"Analysis of diverse optimisation algorithms in breast cancer detection","authors":"K. S. Kumar, K. Venkatalakshmi, K. Karthikeyan, A. Jabeen","doi":"10.1504/IJIM.2018.10014061","DOIUrl":"https://doi.org/10.1504/IJIM.2018.10014061","url":null,"abstract":"Breast cancer is a widespread problem faced by the women in recent years. It is highly essential to detect the breast cancer at an early stage to save lives. Image segmentation technique is used to segment the mistrustful masses from an ultrasound image of the breast. This work focuses on implementation and analysis of various optimisation algorithms in detecting mistrustful masses in the given ultrasound image of the breast. In preprocessing the speckle noise is reduced by using the median filter and contrast is improved by using adaptive histogram equalisation. Particle swarm optimisation, chaotic particle swarm optimisation (CPSO), k-medoids clustering, fuzzy c-means and k-means clustering are used in our work. A comparative analysis has been done using MATLAB and, it is proved that the CPSO has the best result among the others. The accuracy and dice similarity coefficient of the CPSO based method is 93.5793 and 0.8735 respectively.","PeriodicalId":433219,"journal":{"name":"The International Journal on the Image","volume":"48 28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117353531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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