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Automated segmentation and classification technique for brain stroke

N. S. M. Noor, N. M. Saad, A. R. Abdullah, N. M. Ali
2019 International Journal of Electrical and Computer Engineering (IJECE)  
Difussion-Weighted Imaging (DWI) plays an important role in the diagnosis of brain stroke by providing detailed information regarding the soft tissue contrast in the brain organ.  ...  Conventionally, the differential diagnosis of brain stroke lesions is performed manually by professional neuroradiologists during a highly subjective and time- consuming process.  ...  ACKNOWLEDGEMENTS The  ... 
doi:10.11591/ijece.v9i3.pp1832-1841 fatcat:m4ldjvh335eitlbaq4f6xs3354

Performance and Evaluation of Data Mining Techniques in Cancer Diagnosis

R.M. Chandrasekar
2013 IOSR Journal of Computer Engineering  
The experiments are conducted in WEKA.  ...  We analyze the breast Cancer data available from the WBC, WDBC from UCI machine learning with the aim of developing accurate prediction models for breast cancer using data mining techniques.  ...  We also would like to thank the anonymous reviewers for their valuable comments and in sightful suggestions.  ... 
doi:10.9790/0661-1553944 fatcat:c6s5sxo2cbd23idiirwf6ma5wu

A Review on Recent Developments for Detection of Diabetic Retinopathy

Javeria Amin, Muhammad Sharif, Mussarat Yasmin
2016 Scientifica  
Blood vessels detection techniques are also discussed for the diagnosis of proliferative diabetic retinopathy.  ...  In this paper, several techniques for detecting microaneurysms, hemorrhages, and exudates are discussed for ultimate detection of nonproliferative diabetic retinopathy.  ...  The suggested technique showed specificity of 96.85% and sensitivity of 97.25% [2] . A novel technique is proposed for the discovery of bright lesions in color retinal images.  ... 
doi:10.1155/2016/6838976 pmid:27777811 pmcid:PMC5061953 fatcat:vrul355ltjeqvbmgr4quuyflii

Review of Brain Lesion Detection and Classification using Neuroimaging Analysis Techniques

Norhashimah Mohd Saad, Syed Abdul Rahman Syed Abu Bakar, Ahmad Sobri Muda, Musa Mohd Mokji
2015 Jurnal Teknologi  
The objective of this review is to show the recent published techniques and state-of-the-art neuroimaging techniques for the human brain lesions.  ...  The review covers neuroimaging modalities, magnetic resonance imaging, DWI and analysis techniques for CAD in detecting and classifying of brain lesion.  ...  Acknowledgement The author would like to thank Malaysia Ministry of Higher Education (MOHE) for financial assistance while conducting this research.  ... 
doi:10.11113/jt.v74.4670 fatcat:fd4lbfofbbcxdahweew5aj6txe

A Review on Computer Aided Diagnosis of Acute Brain Stroke

Mahesh Anil Inamdar, Udupi Raghavendra, Anjan Gudigar, Yashas Chakole, Ajay Hegde, Girish R. Menon, Prabal Barua, Elizabeth Emma Palmer, Kang Hao Cheong, Wai Yee Chan, Edward J. Ciaccio, U. Rajendra Acharya
2021 Sensors  
The discovery that the affected brain tissue (i.e., 'ischemic penumbra') can be salvaged from permanent damage and the bourgeoning growth in computer aided diagnosis has led to major advances in stroke  ...  status and challenges faced by computer aided diagnosis (CAD), machine learning (ML) and deep learning (DL) based techniques for CT and MRI as prime modalities for stroke detection and lesion region segmentation  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/s21248507 pmid:34960599 pmcid:PMC8707263 fatcat:zc4gtjhkoje2jotcqr5gvlatu4

Landscape of Big Medical Data: A Pragmatic Survey on Prioritized Tasks [article]

Zhifei Zhang, Wanling Gao, Fan Zhang, Yunyou Huang, Shaopeng Dai, Fanda Fan, Jianfeng Zhan, Mengjia Du, Silin Yin, Longxin Xiong, Juan Du, Yumei Cheng, Xiexuan Zhou, Rui Ren (+2 others)
2019 arXiv   pre-print
Fifth, what are the performance gaps of state-of-the-practice and state-of-the-art systems handling big medical data currently or in future?  ...  Third, do the state-of-the-practice and state-of-the-art algorithms perform good jobs? Fourth, are there any benchmarks for measuring algorithms and systems for big medical data?  ...  Nowadays, with the development of techniques, the diagnosis method has improved greatly. First, the development of genomics techniques makes genetic data play an important role in diagnosis.  ... 
arXiv:1901.00642v1 fatcat:fak46q7bgzesll6y4h7i6mcysi

A Review on the use of Artificial Intelligence Techniques in Brain MRI Analysis

Shruti Agarwal, Department of Computer Science Engineering, BBD University, Lucknow, India
2021 Journal of Informatics Electrical and Electronics Engineering (JIEEE)  
This paper gives an overview of the history of AI applications in brain MRI analysis to research its effect at the wider studies discipline and perceive de-manding situations for its destiny.  ...  Analysis of numerous articles to create a taxonomy of research subject matters and results was done. The article is classed which might be posted between 2000 and 2018 with this taxonomy.  ...  The use of many artificial techniques has been applied in almost every medical domain.  ... 
doi:10.54060/jieee/002.02.010 fatcat:gzfzcebf45bn3h5ljcyrbed5xu

Neuroimaging of Epilepsy: Lesions, Networks, Oscillations

E. Abela, C. Rummel, M. Hauf, C. Weisstanner, K. Schindler, R. Wiest
2014 Clinical Neuroradiology  
may help to better understand a range of clinical phenomena such as the type of cognitive impairment, the development of pharmacoresistance, the propagation pathways of seizures, or the success of epilepsy  ...  lesion, across ensembles of functionally and anatomically connected brain areas.  ...  beyond the epileptogenic lesion, across ensembles of functionally and anatomically connected brain areas [15, 16] .  ... 
doi:10.1007/s00062-014-0284-8 pmid:24424576 fatcat:ujziiarzrbhr7kgvgeluemisie

A Comprehensive Review on Medical Diagnosis Using Machine Learning

Kaustubh Arun Bhavsar, Ahed Abugabah, Jimmy Singla, Ahmad Ali AlZubi, Ali Kashif Bashir, Nikita
2021 Computers Materials & Continua  
The unavailability of sufficient information for proper diagnosis, incomplete or miscommunication between patient and the clinician, or among the healthcare professionals, delay or incorrect diagnosis,  ...  The use of machine learning could assist the doctors in making decisions on time, and could also be used as a second opinion or supporting tool.  ...  Figure 1: The process of applying machine learning in disease ML is used in the treatment of patients [7] , as well as prognosis and diagnosis [8] .  ... 
doi:10.32604/cmc.2021.014943 fatcat:zgrkw4he5zhuzhf4fsjyerztge

A Comprehensive Analysis of Recent Deep and Federated-Learning-Based Methodologies for Brain Tumor Diagnosis

Ahmad Naeem, Tayyaba Anees, Rizwan Ali Naqvi, Woong-Kee Loh
2022 Journal of Personalized Medicine  
Artificial intelligence (AI) has recently emerged as an assistive technology for the early diagnosis of tumors, and AI is the primary focus of researchers in the diagnosis of brain tumors.  ...  The primary objective is to explore the performance of deep and federated learning methods and evaluate their accuracy in the diagnosis process.  ...  Methods Applied to Brain Tumor Diagnosis?  ... 
doi:10.3390/jpm12020275 pmid:35207763 pmcid:PMC8880689 fatcat:xat6ux65mvbvldid4frrq6v6jy

Machine learning and glioma imaging biomarkers

T.C. Booth, M. Williams, A. Luis, J. Cardosa, A. Keyoumars, H. Shuaib
2019 Clinical Radiology  
To review how machine learning (ML) is applied to imaging biomarkers in neuro-oncology, in particular for diagnosis, prognosis, and treatment response monitoring.  ...  Although pioneering, most of the evidence is of a low level, having been obtained retrospectively and in single centres.  ...  Acknowledgments This work was supported by the Wellcome/EPSRC Centre for Medical Engineering (WT 203148/Z/16/Z).  ... 
doi:10.1016/j.crad.2019.07.001 pmid:31371027 pmcid:PMC6927796 fatcat:l2epcua3rrdgdowqupwd4cegz4

A Tour of Unsupervised Deep Learning for Medical Image Analysis [article]

Khalid Raza, Nripendra Kumar Singh
2018 arXiv   pre-print
Interpretation of medical images for diagnosis and treatment of complex disease from high-dimensional and heterogeneous data remains a key challenge in transforming healthcare.  ...  In the last few years, both supervised and unsupervised deep learning achieved promising results in the area of medical imaging and image analysis.  ...  Almas Jabeen, and Mr. Nisar Wani for necessary support. Conflict of Interest Statement Authors declare that there is no any conflict of interest in the publication of this manuscript.  ... 
arXiv:1812.07715v1 fatcat:4dd75wfhvnf7db3v72575tikoi

An Update on Machine Learning in Neuro-Oncology Diagnostics [chapter]

Thomas C. Booth
2019 Lecture Notes in Computer Science  
Most of the evidence is low level having been obtained retrospectively and in single centres.  ...  Much research is applied to determining molecular profiles, histological tumour grade and prognosis at the time that patients first present with a brain tumour.  ...  SVM, K-nearest neighbors (KNN), linear discriminant, tree, ensemble, and logistic regression were all independently applied to each set of features.  ... 
doi:10.1007/978-3-030-11723-8_4 fatcat:c7izfhgnxrelbe6ueef7mnihqm

AI-Based Detection, Classification and Prediction/Prognosis in Medical Imaging: Towards Radiophenomics [article]

Fereshteh Yousefirizi, Pierre Decazes, Amine Amyar, Su Ruan, Babak Saboury, Arman Rahmim
2022 arXiv   pre-print
Radiomics analysis has the potential to be utilized as a noninvasive technique for the accurate characterization of tumors to improve diagnosis and treatment monitoring.  ...  We also discuss needed efforts to enable the translation of AI techniques to routine clinical workflows, and potential improvements and complementary techniques such as the use of natural language processing  ...  Acknowledgements This project was in part supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant RGPIN-2019-06467, and the Canadian Institutes of Health Research  ... 
arXiv:2110.10332v4 fatcat:vmpxhoolarbrve5ddyfn5umfim

Organization and hierarchy of the human functional brain network lead to a chain-like core [article]

Rossana Mastrandrea, Andrea Gabrielli, Fabrizio Piras, Gianfranco Spalletta, Guido Caldarelli, Tommaso Gili
2017 arXiv   pre-print
We also report the hierarchy of network segregation and the level of clusters integration as a function of the connectivity strength between brain regions.  ...  Complex network theory allows to elicit the functional architecture of the brain in terms of links (correlations) between nodes (grey matter regions) and to extract information out of the noise.  ...  , (4) the presence of any brain abnormality and microvascular lesion apparent on conventional FLAIR-scans.  ... 
arXiv:1701.04782v1 fatcat:xrmgju7zbjhphhq4rty6r2fvye
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