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Region Of Interest Based Image Classification: A Study in MRI Brain Scan Categorization [chapter]

Ashraf Elsayed, Frans Coenen, Marta Garca-Fiana, Vanessa Sluming
2012 Data Mining Applications in Engineering and Medicine  
The four proposed techniques for classifying MRI brain scan data according to a single object that occurs across the data, are founded on weighted graph mining, time series analysis, the Hough transform  ...  In the context of image analysis the Hough transform is principally used for the purpose of detecting parametric shapes (boxes, cylinders, cones, etc.) in image data.  ... 
doi:10.5772/50019 fatcat:kpxf6fpq4zb7pbrkjgultlmbza

A Survey on Detecting Brain Tumorinmri Images Using Image Processing Techniques

A.Sin dhu, S.Me era
2015 International Journal of Innovative Research in Computer and Communication Engineering  
Fig 1 shows the MRI image containing tumor which can also define the tumor type.This work will be extendedfor Median Filter and Region Based algorithms to detect the types of tumor in MRI which will provide  ...  Medical Image techniques are used for Medical diagnosis. Brain tumor is a serious life threatening disease.  ...  Texture. shape based features LINEAR DISCRIMIN ANT ANALYSIS 98.87% [22]  ... 
doi:10.15680/ijircce.2015.0301030 fatcat:fjmm3tmztrawxjhnplr4dninpy

Region of Interest Based Image Classification using time series analysis

A. Elsayed, F. Coenen, M. Garcia-Finana, V. Sluming
2010 The 2010 International Joint Conference on Neural Networks (IJCNN)  
An approach to Region Of Interest Based Image Classification (ROIBIC), based on a time series analysis approach, is described.  ...  Comparisons are also presented with a graph based ROIBIC approach. Ashraf Elsayed is with the  ...  II TCV II CLASSIFICATION ACCURACY (%) USING GRAPH BASED ROIBICTABLE III CLASSIFICATION ACCURACY (%) USING TIME SERIES ROIBIC FOR DIFFERENT TRAINING-TEST SET DISTRIBUTIONS Support Threshold (%) Levels  ... 
doi:10.1109/ijcnn.2010.5596324 dblp:conf/ijcnn/ElsayedCGS10 fatcat:hz4tqldg5nfwbjvvzwhi5pkcmi

Region of Interest Based Image Categorization [chapter]

Ashraf Elsayed, Frans Coenen, Marta García-Fiñana, Vanessa Sluming
2010 Lecture Notes in Computer Science  
The second approach is founded on a time series analysis technique whereby the ROI are represented as time series which can then be used as the foundation for a Case Based Reasoner.  ...  Region Of Interest Based Image Classification (ROIBIC) is a mechanism for categorising images according to some specific component or object that features across a given image set.  ...  The Dynamic Time Warping Algorithm DTW [2] is a time series analysis technique for comparing curves.  ... 
doi:10.1007/978-3-642-15105-7_19 fatcat:s4cfbhsqzffmng4oejygso6msy

Computer-Aided Knee Joint Magnetic Resonance Image Segmentation - A Survey [article]

Boyu Zhang, Yingtao Zhang, H. D. Cheng, Min Xian, Shan Gai, Olivia Cheng, Kuan Huang
2018 arXiv   pre-print
MRI is the most popular technology to observe and evaluate the progress of OA course. However, the extreme labor cost of MRI analysis makes the process inefficient and expensive.  ...  which has immense potential for both clinic and scientific research.  ...  [30] [31] [32] , classification-based methods [33] [34] [35] [36] [37] , and graph-based methods [38] [39] [40] , etc.  ... 
arXiv:1802.04894v1 fatcat:zodyczjmj5h7xotqceixu76lkm

Predict Alzheimer's disease using hippocampus MRI data: a lightweight 3D deep convolutional network model with visual and global shape representations

Sreevani Katabathula, Qinyong Wang, Rong Xu
2021 Alzheimer's Research & Therapy  
We have recently developed DenseCNN, a lightweight 3D deep convolutional network model, for AD classification based on hippocampus magnetic resonance imaging (MRI) segments.  ...  diagnostic tool for AD classification.  ...  Acknowledgements We thank the Alzheimer's Disease Neuroimaging Initiative (ADNI) for generously sharing clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's  ... 
doi:10.1186/s13195-021-00837-0 pmid:34030743 fatcat:ujjf6osodzcnbnq3btnsp7z6am

Graph based MRI brain scan classification and correlation discovery

S. Seth Long, Lawrence B. Holder
2012 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)  
We find that whole-brain analysis in this manner allows automatic classification of images based on gender if the whole brain is included, but not strictly based on the ventricular system.  ...  In this paper, we use a graph-based approach to represent the shape of the brain, including the shape of the ventricular system and shape relative to the skull.  ...  [2] have used graph-based shape representation to classify MR images using the 2D shape of the corpus callosum as it appears in a midsaggital section.  ... 
doi:10.1109/cibcb.2012.6217249 dblp:conf/cibcb/LongH12 fatcat:73wwcjqtgvfbnas5ezrhxvayje

A Review on Image- and Network-based Brain Data Analysis Techniques for Alzheimer's Disease Diagnosis Reveals a Gap in Developing Predictive Methods for Prognosis [article]

Mayssa Soussia, Islem Rekik
2018 arXiv   pre-print
In this study, we reviewed neuroimaging-based technical methods developed for AD and mild-cognitive impairment (MCI) classification and prediction tasks, selected by screening all MICCAI proceedings published  ...  Over the past years, neuroimaging techniques paved the way for computer-based diagnosis and prognosis to facilitate the automation of medical decision support and help clinicians identify cognitively intact  ...  As such, the use of advanced network and shape analysis methods, using machine learning, could prove fruitful for both classification [47, 48, 49, 50] and prediction tasks.  ... 
arXiv:1808.01951v1 fatcat:zj2p6w5xw5abbdfhhs6ubfzz74

Multimodel Image Segmentation and Classification by MAP based graph cut and Improved VGG16

2020 International Journal of Engineering and Advanced Technology  
The paper mainly focused on the employment of a suitable proposed algorithm to adopt both the CT and MRI images for precise segmentation and classification.  ...  In general most of the prevailing algorithms is suited for the predicted of the image only employing the MRI or CT image.  ...  Objective • To frame an efficient segmentation and classification technique which could apply to both CT and MRI brain images • To segment, the provided image by map base Graph cut segmentation technique  ... 
doi:10.35940/ijeat.d7472.069520 fatcat:v74hct6av5d7dcok7kfuwvb2x4

Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future

David Ahmedt-Aristizabal, Mohammad Ali Armin, Simon Denman, Clinton Fookes, Lars Petersson
2021 Sensors  
We provide an overview of these methods in a systematic manner, organized by their domain of application including functional connectivity, anatomical structure, and electrical-based analysis.  ...  We also outline the limitations of existing techniques and discuss potential directions for future research.  ...  [37] proposed a synergic graph-based model for a normal/abnormal classification of brain MRI images.  ... 
doi:10.3390/s21144758 fatcat:jytyt4u2pjgvhnhcto3vcvd3a4

Graph Based Classification of MRI Data Based on the Ventricular System

S. Seth Long, Lawrence B. Holder
2011 2011 IEEE 11th International Conference on Data Mining Workshops  
This paper describes the use of trees to represent the 3D space containing the third and lateral ventricles, and classification of these trees using frequent subgraph mining and support vector machines  ...  Level of cognitive impairment and years of education are shown to be predictable given a tree representation of the shape of the third and lateral ventricles, demonstrating that the shape of the ventricular  ...  GRAPH-BASED SHAPE CLASSIFICATION A.  ... 
doi:10.1109/icdmw.2011.90 dblp:conf/icdm/LongH11 fatcat:hak7kzg2q5eotjyw42ivurg6v4

Image Enhancement and Segmentation Techniques for Detection of Knee Joint Diseases: A Survey

Tanzila Saba, Amjad Rehman, Zahid Mehmood, Hoshang Kolivand, Muhammad Sharif
2018 Current Medical Imaging Reviews  
The focus of current research is MRI-based medical image analysis for knee bone disease detection.  ...  Normally, the knee cancers are pointed out with the help of different MRI analysis techniques and latter image analysis strategies understand these images.  ...  [67] 2014 A graph cut based segmentation method with novel label refinement and shape prior.  ... 
doi:10.2174/1573405613666170912164546 fatcat:tgrtyuhi6nh6zmrkiqstmiwp5m

Brain tumor classification and diagnosis techniques

Wedad Abdul Khuder Naser *
2022 Global Journal of Engineering and Technology Advances  
On MRI pictures, there are several techniques for classification and detecting a brain tumor region.  ...  We present background reviews of many proposed techniques for detecting brain tumors in this paper. There is a lot of literature on diagnosing and improving the accuracy of this type of brain tumor.  ...  Acknowledgments The authors would like to thank the Mustansiriyah University ( Baghdad, Iraq for supporting this work.  ... 
doi:10.30574/gjeta.2022.10.2.0036 fatcat:34zoa4fsmbfkteswkd3exwiyva

Multi-atlas segmentation of subcortical brain structures via the AutoSeg software pipeline

Jiahui Wang, Clement Vachet, Ashley Rumple, Sylvain Gouttard, Clémentine Ouziel, Emilie Perrot, Guangwei Du, Xuemei Huang, Guido Gerig, Martin Styner
2014 Frontiers in Neuroinformatics  
A directed graph with edge weights based on intensity and shape similarity between all MR scans is then computed. The set of neighboring templates is selected via clustering of the graph.  ...  The multi-atlas-based AutoSeg has been evaluated on subcortical structure segmentation with a testing dataset of 20 adult brain MRI scans and 15 atlas MRI scans.  ...  In this study, the MRI scans were selected from OASIS database, which was supported by P50 AG05681, P01 AG03991, R01 AG021910, P50 MH071616, U24 RR021382, R01 MH56584.  ... 
doi:10.3389/fninf.2014.00007 pmid:24567717 pmcid:PMC3915103 fatcat:eqw4unvds5du3k4baexwejd6ja

Tumor Diagnosis in MRI Brain Image using ACM Segmentation and ANN-LM Classification Techniques

A. Shenbagarajan, V. Ramalingam, C. Balasubramanian, S. Palanivel
2016 Indian Journal of Science and Technology  
In this proposed MRI image analysis using the region based Active Contour Method (ACM) used for segmentation and Artificial Neural Network (ANN) based Levenberg-Marquardt (LM) algorithm used for classification  ...  Application: The proposed MRI image based brain tumour analysis would efficiently deal with segmentation and classification process for brain tumour analysis with use of feature extraction methods, so  ...  After shape feature extraction, these two features independently are used for classification step in MRI brain image analysis.  ... 
doi:10.17485/ijst/2016/v9i1/78766 fatcat:4fo3qmnkznhbzk3yuejjb3bxdy
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