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The Imaging Science Journal Volume 65, 2017 - Issue 2
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Articles

A novel approach for characterisation of ischaemic stroke lesion using histogram bin-based segmentation and gray level co-occurrence matrix features

R. KanchanaSchool of Electronics Engineering, VIT University, Chennai Campus, Tamil Nadu, India
&
R. MenakaSchool of Electronics Engineering, VIT University, Chennai Campus, Tamil Nadu, IndiaCorrespondence[email protected]
Pages 124-136 | Received 25 Oct 2016, Accepted 10 Feb 2017, Published online: 13 Mar 2017

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Santwana Gudadhe & Anuradha Thakare. (2023) Multivariate Analysis of Ischaemic Lesions Using Computed Tomography and CT Perfusion Imaging: Critical Review. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization 0:0, pages 1-16.
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Articles from other publishers (7)

Anis Azwani Muhd Suberi, Wan Nurshazwani Wan Zakaria, Nik Farhan Nik Fuad, Razali Tomari, Ain Nazari & Fakhrul Razan Rahmad. 2021. Handbook of Decision Support Systems for Neurological Disorders. Handbook of Decision Support Systems for Neurological Disorders 203 221 .
Anis Azwani Muhd Suberi, Wan Nurshazwani Wan Zakaria, Razali Tomari, Ain Nazari, Nik Farhan Nik Fuad, Fakhrul Razan Rahmad & Salsabella Mohd Fizol. 2021. Proceedings of the 11th National Technical Seminar on Unmanned System Technology 2019. Proceedings of the 11th National Technical Seminar on Unmanned System Technology 2019 805 817 .
R. Kanchana & R. Menaka. (2020) Ischemic stroke lesion detection, characterization and classification in CT images with optimal features selection. Biomedical Engineering Letters 10:3, pages 333-344.
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Paul Mikhail, Michael Gia Duy Le & Grant Mair. (2020) Computational Image Analysis of Nonenhanced Computed Tomography for Acute Ischaemic Stroke: A Systematic Review. Journal of Stroke and Cerebrovascular Diseases 29:5, pages 104715.
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Luis Garcia-Temza, Jose L. Risco-Martin, Jose L. Ayala, Gemma Reig Rosello & Juan M. Camarasaltas. (2019) Comparison of Different Machine Learning Approaches to Model Stroke Subtype Classification and Risk Prediction. Comparison of Different Machine Learning Approaches to Model Stroke Subtype Classification and Risk Prediction.
Praveen Gurunath Bharathi, Anita Agrawal, Ponraj Sundaram & Sanjay Sardesai. (2019) Combination of hand-crafted and unsupervised learned features for ischemic stroke lesion detection from Magnetic Resonance Images. Biocybernetics and Biomedical Engineering 39:2, pages 410-425.
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G.B. Praveen, Anita Agrawal, Ponraj Sundaram & Sanjay Sardesai. (2018) Ischemic stroke lesion segmentation using stacked sparse autoencoder. Computers in Biology and Medicine 99, pages 38-52.
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