Ischemic Stroke Segmentation on CT Images Using Joint Features

doi:10.15388/Informatica.2004.060

2011 IEEE International Conference on Signal and Image Processing Applications (ICSIPA)

Mehdi Sajjadi, Rassoul Amirfattahi, Mohammad Reza Ahmadzadeh, Mohammad Ali Saghafi

https://doi.org/10.1109/ICSIPA.2011.6144120

Conference: (2011), p. 384

Feature Ranking of Spatial Domain Features for Efficient Characterization of Stroke Lesions

Anish Mukherjee, Abhishek Kanaujia, R. Karthik

https://doi.org/10.1007/978-981-10-8354-9_14

Book: Lecture Notes in Electrical Engineering (Computational Signal Processing and Analysis) Volume 490 (2018), p. 149

2023 International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)

S. Manikandan, Anitha. G, Josiah Samuel Raj. J

https://doi.org/10.1109/ACCAI58221.2023.10200194

Conference: (2023), p. 1

Automatic Detection and Classification of Ischemic Stroke Using K-Means Clustering and Texture Features

N. Hema Rajini, R. Bhavani

https://doi.org/10.4018/978-1-4666-9685-3.ch018

Book: Advances in Computational Intelligence and Robotics (Emerging Technologies in Intelligent Applications for Image and Video Processing) (2016), p. 441

2016 Global Medical Engineering Physics Exchanges/Pan American Health Care Exchanges (GMEPE/PAHCE)

M.G. Ruano, E. Hajimani, A. E. Ruano

https://doi.org/10.1109/GMEPE-PAHCE.2016.7504656

Conference: (2016), p. 1

2015 IEEE 9th International Symposium on Intelligent Signal Processing (WISP) Proceedings

Elmira Hajimani, M. G. Ruano, A. E. Ruano

https://doi.org/10.1109/WISP.2015.7139170

Conference: (2015), p. 1

2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

M. Chawla, S. Sharma, J. Sivaswamy, L.T. Kishore

https://doi.org/10.1109/IEMBS.2009.5335289

Conference: (2009), p. 3581

Context-Aware Convolutional Neural Networks for Stroke Sign Detection in Non-contrast CT Scans

Aneta Lisowska, Alison O’Neil, Vismantas Dilys, Matthew Daykin, Erin Beveridge, Keith Muir, Stephen Mclaughlin, Ian Poole

https://doi.org/10.1007/978-3-319-60964-5_43

Book: Communications in Computer and Information Science (Medical Image Understanding and Analysis) Volume 723 (2017), p. 494

2006 International Biennial Baltic Electronics Conference

A. Usinskas, R. Gleizniene

https://doi.org/10.1109/BEC.2006.311103

Conference: (2006), p. 1

A Quantitative Method Using Head Noncontrast CT Scans to Detect Hyperacute Nonvisible Ischemic Changes in Patients With Stroke

Ryszard S. Gomolka, Robert M. Chrzan, Andrzej Urbanik, Wieslaw L. Nowinski

https://doi.org/10.1111/jon.12363

Journal: Journal of Neuroimaging Volume 26, Issue 6 (2016), p. 581

A region-based segmentation of tumour from brain CT images using nonlinear support vector machine classifier

A. Padma Nanthagopal, R. Sukanesh Rajamony

https://doi.org/10.3109/03091902.2012.682638

Journal: Journal of Medical Engineering & Technology Volume 36, Issue 5 (2012), p. 271

Acute ischemic stroke lesion core segmentation in CT perfusion images using fully convolutional neural networks

Albert Clèrigues, Sergi Valverde, Jose Bernal, Jordi Freixenet, Arnau Oliver, Xavier Lladó

https://doi.org/10.1016/j.compbiomed.2019.103487

Journal: Computers in Biology and Medicine Volume 115 (2019), p. 103487

An intelligent support system for automatic detection of cerebral vascular accidents from brain CT images

Elmira Hajimani, M.G. Ruano, A.E. Ruano

https://doi.org/10.1016/j.cmpb.2017.05.005

Journal: Computer Methods and Programs in Biomedicine Volume 146 (2017), p. 109

Application of Machine Learning Techniques for Characterization of Ischemic Stroke with MRI Images: A Review

Asit Subudhi, Pratyusa Dash, Manoranjan Mohapatra, Ru-San Tan, U. Rajendra Acharya, Sukanta Sabut

https://doi.org/10.3390/diagnostics12102535

Journal: Diagnostics Volume 12, Issue 10 (2022), p. 2535

Automated Cerebral Infarct Detection on Computed Tomography Images Based on Deep Learning

Syu-Jyun Peng, Yu-Wei Chen, Jing-Yu Yang, Kuo-Wei Wang, Jang-Zern Tsai

https://doi.org/10.3390/biomedicines10010122

Journal: Biomedicines Volume 10, Issue 1 (2022), p. 122

Automated delineation of stroke lesions using brain CT images

Céline R. Gillebert, Glyn W. Humphreys, Dante Mantini

https://doi.org/10.1016/j.nicl.2014.03.009

Journal: NeuroImage: Clinical Volume 4 (2014), p. 540

Automated emergency paramedical response system

Mashrin Srivastava, Saumya Suvarna, Apoorva Srivastava, S. Bharathiraja

https://doi.org/10.1007/s13755-018-0061-1

Journal: Health Information Science and Systems Volume 6, Issue 1 (2018)

Automated quantification of cerebral edema following hemispheric infarction: Application of a machine-learning algorithm to evaluate CSF shifts on serial head CTs

Yasheng Chen, Rajat Dhar, Laura Heitsch, Andria Ford, Israel Fernandez-Cadenas, Caty Carrera, Joan Montaner, Weili Lin, Dinggang Shen, Hongyu An, Jin-Moo Lee

https://doi.org/10.1016/j.nicl.2016.09.018

Journal: NeuroImage: Clinical Volume 12 (2016), p. 673

Automated stroke lesion segmentation in non-contrast CT scans using dense multi-path contextual generative adversarial network

Hulin Kuang, Bijoy K Menon, Wu Qiu

https://doi.org/10.1088/1361-6560/aba166

Journal: Physics in Medicine & Biology Volume 65, Issue 21 (2020), p. 215013

Combination of hand-crafted and unsupervised learned features for ischemic stroke lesion detection from Magnetic Resonance Images

Praveen Gurunath Bharathi, Anita Agrawal, Ponraj Sundaram, Sanjay Sardesai

https://doi.org/10.1016/j.bbe.2019.01.003

Journal: Biocybernetics and Biomedical Engineering Volume 39, Issue 2 (2019), p. 410

Computer aided detection and diagnosis methodology for brain stroke using adaptive neuro fuzzy inference system classifier

Selladurai Anbumozhi

https://doi.org/10.1002/ima.22380

Journal: International Journal of Imaging Systems and Technology Volume 30, Issue 1 (2020), p. 196

Computer aided detection of ischemic stroke using segmentation and texture features

N. Hema Rajini, R. Bhavani

https://doi.org/10.1016/j.measurement.2013.01.010

Journal: Measurement Volume 46, Issue 6 (2013), p. 1865

Computer-aided detection and characterization of stroke lesion – a short review on the current state-of-the art methods

R. Karthik, R. Menaka

https://doi.org/10.1080/13682199.2017.1370879

Journal: The Imaging Science Journal Volume 66, Issue 1 (2018), p. 1

Development of a Graphical User Interface Training System for Early Infarct Detection

Chung Sheng Ee, Fung Fung Ting, Kok Swee Sim, Chih Ping Tso

https://doi.org/10.18178/ijiee.2016.6.1.594

Journal: International Journal of Information and Electronics Engineering (2015), p. 54

Efficient multi-kernel DCNN with pixel dropout for stroke MRI segmentation

Liangliang Liu, Fang-Xiang Wu, Jianxin Wang

https://doi.org/10.1016/j.neucom.2019.03.049

Journal: Neurocomputing Volume 350 (2019), p. 117

Identification of invisible ischemic stroke in noncontrast CT based on novel two‐stage convolutional neural network model

Guoqing Wu, Xi Chen, Jixian Lin, Yuanyuan Wang, Jinhua Yu

https://doi.org/10.1002/mp.14691

Journal: Medical Physics Volume 48, Issue 3 (2021), p. 1262

Ischemic Stroke Detection System with a Computer-Aided Diagnostic Ability Using an Unsupervised Feature Perception Enhancement Method

Yeu-Sheng Tyan, Ming-Chi Wu, Chiun-Li Chin, Yu-Liang Kuo, Ming-Sian Lee, Hao-Yan Chang

https://doi.org/10.1155/2014/947539

Journal: International Journal of Biomedical Imaging Volume 2014 (2014), p. 1

Ischemic infarct detection, localization, and segmentation in noncontrast CT human brain scans: review of automated methods

Wieslaw L. Nowinski, Jerzy Walecki, Gabriela Półtorak-Szymczak, Katarzyna Sklinda, Bartosz Mruk

https://doi.org/10.7717/peerj.10444

Journal: PeerJ Volume 8 (2020), p. e10444

Medical image analysis methods in MR/CT-imaged acute-subacute ischemic stroke lesion: Segmentation, prediction and insights into dynamic evolution simulation models. A critical appraisal

Islem Rekik, Stéphanie Allassonnière, Trevor K. Carpenter, Joanna M. Wardlaw

https://doi.org/10.1016/j.nicl.2012.10.003

Journal: NeuroImage: Clinical Volume 1, Issue 1 (2012), p. 164

Recovery of CT stroke hypodensity – An adaptive variational approach

Artur Przelaskowski

https://doi.org/10.1016/j.compmedimag.2015.03.006

Journal: Computerized Medical Imaging and Graphics Volume 46 (2015), p. 131

Segmenting Hemorrhagic and Ischemic Infarct Simultaneously From Follow-Up Non-Contrast CT Images in Patients With Acute Ischemic Stroke

Hulin Kuang, Bijoy K. Menon, Wu Qiu

https://doi.org/10.1109/ACCESS.2019.2906605

Journal: IEEE Access Volume 7 (2019), p. 39842

Semi‐automated infarct segmentation from follow‐up noncontrast CT scans in patients with acute ischemic stroke

Hulin Kuang, Bijoy K. Menon, Wu Qiu

https://doi.org/10.1002/mp.13703

Journal: Medical Physics Volume 46, Issue 9 (2019), p. 4037

Separability of Acute Cerebral Infarction Lesions in CT Based Radiomics: Toward Artificial Intelligence-Assisted Diagnosis

Yun Guan, Peng Wang, Qi Wang, Peihao Li, Jianchao Zeng, Pinle Qin, Yanfeng Meng, Zhiguo Zhou

https://doi.org/10.1155/2020/8864756

Journal: BioMed Research International Volume 2020 (2020), p. 1

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