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Spatial regularization of SVM for the detection of diffusion alterations associated with stroke outcome

Rémi Cuingnet, Charlotte Rosso, Marie Chupin, Stéphane Lehéricy, Didier Dormont, Habib Benali, Yves Samson, Olivier Colliot
2011 Medical Image Analysis  
It was then applied to 72 stroke patients to detect brain areas associated with motor outcome at 90 days, based on diffusionweighted images acquired at the acute stage (median delay one day).  ...  In this paper, we propose a new method to detect differences at the group level in brain images based on spatially regularized support vector machines (SVM).  ...  Acknowledgments This work was partially supported by the ''Programme Hospitalier de Recherche Clinique EVAL-USINV'' (No. AOM 03 008). This work was partially supported by ANR (Project HM-TC, No.  ... 
doi:10.1016/j.media.2011.05.007 pmid:21752695 fatcat:5wjjk6q7sbgzjm6ayw6qrcrw5u

Spatially Regularized SVM for the Detection of Brain Areas Associated with Stroke Outcome [chapter]

Rémi Cuingnet, Charlotte Rosso, Stéphane Lehéricy, Didier Dormont, Habib Benali, Yves Samson, Olivier Colliot
2010 Lecture Notes in Computer Science  
We then applied it to 72 stroke patients to detect brain areas associated with motor outcome at 90 days, based on diffusion-weighted images acquired at the acute stage (one day delay).  ...  First, we propose to spatially regularize the SVM using a graph encoding the voxels' proximity. Two examples of regularization graphs are provided.  ...  We then applied it on real data to the detection of brain areas associated with stroke outcome based on diffusion-weighted MRI acquired at the acute stage.  ... 
doi:10.1007/978-3-642-15705-9_39 fatcat:eant7pkgyjef3nzmknpudg3uqu

Computational Analysis: A Bridge to Translational Stroke Treatment [chapter]

Nirmalya Ghosh, Yu Sun, Christine Turenius, Bir Bhanu, Andre Obenaus, Stephen Ashwal
2012 Translational Stroke Research  
We conclude with our assessment of probable future research directions in the fi eld of computational noninvasive stroke analysis such as automated detection of the ischemic core and penumbra, monitoring  ...  Objective rapid quantifi cation of injury using computational methods can improve the assessment of the degree of stroke injury, aid in the selection of patients for early or specifi c treatments, and  ...  SVM detected core and penumbra from T2 and ADC maps (after spatial coregistration) at 4 days post injury.  ... 
doi:10.1007/978-1-4419-9530-8_42 fatcat:did4nx25jzgkjjt4onmamkytjm

Anatomical Brain Networks on the Prediction of Abnormal Brain States

Yasser Iturria-Medina
2013 Brain Connectivity  
, the interconnections between gray matter regions are altered (e.g., due to the presence of diseases such as schizophrenia, stroke, multiple sclerosis, and dementia).  ...  network alterations associated to specific brain disorders.  ...  Monahan, Alejandro Pérez Fernández, María Antonieta Bobes, Eduardo Gonzalez Alemañ y, Mitchell Valdés Sosa, and the anonymous reviewers for their helpful suggestions and comments on the manuscript.  ... 
doi:10.1089/brain.2012.0122 pmid:23249224 fatcat:bujls77bb5fdtivilt5iqbhatu

Advance Machine Learning Methods for Dyslexia Biomarker Detection: A Review of Implementation Details and Challenges

Opeyemi Lateef Usman, Ravie Chandren Muniyandi, Khairuddin Omar, Mazlyfarina Mohamad
2021 IEEE Access  
The review is conducted within the premise of implementation and experimental outcomes for each of the 22 selected articles using the Preferred Reporting Items for Systematic review and Meta-Analyses (  ...  PRISMA) protocol, with a view to outlining some critical challenges for achieving high accuracy and reliability of the state-of-the-art machine learning methods.  ...  ACKNOWLEDGMENT The authors would like to appreciate the support of Universiti Kebangsaan Malaysia (UKM).  ... 
doi:10.1109/access.2021.3062709 fatcat:u5xr6p4ubbeollvfmo7l5mgu6a

Characterizing the Structural Pattern of Heavy Smokers Using Multivoxel Pattern Analysis

Yufeng Ye, Jian Zhang, Bingsheng Huang, Xun Cai, Panying Wang, Ping Zeng, Songxiong Wu, Jinting Ma, Han Huang, Heng Liu, Guo Dan, Guangyao Wu
2021 Frontiers in Psychiatry  
Such findings might provide insights for understanding the mechanism of chronic smoking and the creation of effective cessation treatment.  ...  In this study, a multivoxel pattern analysis using a searchlight algorithm and support vector machine was applied on structural magnetic resonance imaging to identify the spatial pattern of gray matter  ...  ACKNOWLEDGMENTS The authors want to thank the Zhongnan Hospital of Wuhan University and the participants who took part in the study and data collection.  ... 
doi:10.3389/fpsyt.2020.607003 pmid:33613332 pmcid:PMC7890259 fatcat:lg47w65uybcgbgpc5ky7j67xny

MR Images, Brain Lesions, and Deep Learning

Darwin Castillo, Vasudevan Lakshminarayanan, María José Rodríguez-Álvarez
2021 Applied Sciences  
For the selection criteria, we used bibliometric networks. Of a total of 140 documents, we selected 38 articles that deal with the main objectives of this study.  ...  In the present work, we review the published literature on systems and algorithms that allow for classification, identification, and detection of white matter hyperintensities (WMHs) of brain magnetic  ...  A method for detecting stroke presence using the SVM and feed-forward backpropagation neural network classifiers is presented in [21] .  ... 
doi:10.3390/app11041675 fatcat:ivwi2tp52ngstdoelbsjglhem4

Reducing CSF Partial Volume Effects to Enhance Diffusion Tensor Imaging Metrics of Brain Microstructure

Lauren E. Salminen, Thomas E. Conturo, Jacob D. Bolzenius, Ryan P. Cabeen, Erbil Akbudak, Robert H. Paul
2016 Technology & Innovation  
While this field originated with techniques capable of capturing macrostructural details of brain anatomy, modern methods such as diffusion tensor imaging (DTI) that are now regularly implemented in research  ...  Technological advances over recent decades now allow for in vivo observation of human brain tissue through the use of neuroimaging methods.  ...  ACKNOWLEDGMENTS This work was supported by the National Institutes of Health/National Institute of Neurological Disorders and Stroke grant numbers R01 NS052470 and R01 NS039538 and the National Institutes  ... 
doi:10.21300/18.1.2016.5 pmid:27721931 pmcid:PMC5054978 fatcat:cre32m6nnzbr5hsvdehamoc6sm

A Survey on Classification algorithms of Brain Images in Alzheimer's disease based on Feature Extraction techniques

Ruhul Amin Hazarika, Arnab Kumar Maji, Samarendra Nath Sur, Babu Sena Paul, Debdatta Kandar
2021 IEEE Access  
The hyper graph-based regularization for the proposed method is designed for unambiguous illustration of the association in all the modalities, such as MRI and PET.  ...  Busy textures are those for which there are rapid changes of intensities from one pixel to its neighbor. The spatial frequency of intensity alteration is very high.  ... 
doi:10.1109/access.2021.3072559 fatcat:cc4ffd325naozaxs63geaut76i

Brain-Computer Interface: Advancement and Challenges

M F Mridha, Sujoy Chandra Das, Muhammad Mohsin Kabir, Aklima Akter Lima, Md Rashedul Islam, Yutaka Watanobe
2021 Sensors  
Finally, the paper investigates several unsolved challenges of the BCI and explains them with possible solutions.  ...  Hence, a comprehensive overview of the BCI domain is presented in this study. This study covers several applications of BCI and upholds the significance of this domain.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s21175746 pmid:34502636 pmcid:PMC8433803 fatcat:gt5v46mr5nhjvptosklmvq2ria

Medical Big Data: Neurological Diseases Diagnosis Through Medical Data Analysis

Siuly Siuly, Yanchun Zhang
2016 Data Science and Engineering  
Acknowledgments This work is supported by the National Natural Science Foundation of China (NSFC 61332013) and the Australian Research Council (ARC) Linkage Project (LP100200682) and Discovery Project  ...  Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecomm ons.org/licenses/by/4.0/), which permits unrestricted use, distribution  ...  [84] discussed common arrhythmias during and following a stroke event, and the hemodynamic changes associated with acute stroke.  ... 
doi:10.1007/s41019-016-0011-3 fatcat:gdebiikzjvghjaegsggrpmz24q

Deep Learning Paradigm for Cardiovascular Disease/Stroke Risk Stratification in Parkinson's Disease Affected by COVID-19: A Narrative Review

Jasjit S. Suri, Mahesh A. Maindarkar, Sudip Paul, Puneet Ahluwalia, Mrinalini Bhagawati, Luca Saba, Gavino Faa, Sanjay Saxena, Inder M. Singh, Paramjit S. Chadha, Monika Turk, Amer Johri (+31 others)
2022 Diagnostics  
Method: The PRISMA search strategy was used for the selection of 292 studies closely associated with the effect of PD on CVD risk in the COVID-19 framework.  ...  Lastly, we examined the artificial intelligence bias and provided recommendations for early detection of CVD/stroke in PD patients in the presence of COVID-19.Conclusion: The DL is a very powerful tool  ...  [252] explained the significance of comorbidity appears to be associated with adverse outcomes in COVID-19 patients.  ... 
doi:10.3390/diagnostics12071543 pmid:35885449 pmcid:PMC9324237 fatcat:rrhkppghkfayfbnlsyx7hq7koa

Brain Tumor Characterization Using Radiogenomics in Artificial Intelligence Framework

Biswajit Jena, Sanjay Saxena, Gopal Krishna Nayak, Antonella Balestrieri, Neha Gupta, Narinder N. Khanna, John R. Laird, Manudeep K. Kalra, Mostafa M. Fouda, Luca Saba, Jasjit S. Suri
2022 Cancers  
The substantial brain tumor characterization includes the identification of the molecular signature of various useful genomes whose alteration causes the brain tumor.  ...  Brain tumor characterization (BTC) is the process of knowing the underlying cause of brain tumors and their characteristics through various approaches such as tumor segmentation, classification, detection  ...  ; hence, it is often used in the detection of tumors, strokes, and hemorrhage.  ... 
doi:10.3390/cancers14164052 pmid:36011048 pmcid:PMC9406706 fatcat:iwo6a7plnjgujgt6mi7wfywo3u

Applications of Deep Learning and Reinforcement Learning to Biological Data

Mufti Mahmud, Mohammed Shamim Kaiser, Amir Hussain, Stefano Vassanelli
2018 IEEE Transactions on Neural Networks and Learning Systems  
Rapid advances of hardware-based technologies during the past decades have opened up new possibilities for Life scientists to gather multimodal data in various application domains (e.g., Omics, Bioimaging  ...  This review article provides a comprehensive survey on the application of DL, RL, and Deep RL techniques in mining Biological data.  ...  Acknowledgment The authors would like to thank Dr. Pawel Raif and Dr. Kamal Abu-Hassan for useful discussions during the early stage of the work.  ... 
doi:10.1109/tnnls.2018.2790388 pmid:29771663 fatcat:6r63zihrfvea7cto4ei3mlvqtu

A REVIEW STUDY OF METHODS UTILIZED FOR IDENTIFYING AND SEGMENTING THE BRAIN TUMOR FROM MR IMAGERIES

MOHD SHAFRY MOHD RAHIM AHMED SAIFULLAH SAMI
2019 Zenodo  
The processes delimit the accuracy levels leading to the identification of the need for the provision of additional time considered necessary in meeting the stipulated needs of the process.  ...  Also integrate a comparative study of the automated brain tumor coupled through the utilization of tuomr detection techniques.  ...  The vital benefit obtained with the procedure applied was its capability in altering the input fed into the system in accordance with the outcome achieved in the previous trial that was fed in as feedback  ... 
doi:10.5281/zenodo.3256441 fatcat:xiqd75juvbbhnjbwffgruujnbi
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