An Effective Approach for Sub-acute Ischemic Stroke Lesion Segmentation by Adopting Meta-Heuristics Feature Selection Technique Along with Hybrid Naive Bayes and Sample-Weighted Random Forest Classification-Reference-Cited by-同舟云学术

An Effective Approach for Sub-acute Ischemic Stroke Lesion Segmentation by Adopting Meta-Heuristics Feature Selection Technique Along with Hybrid Naive Bayes and Sample-Weighted Random Forest Classification

Published:2019-03-08 Issue:1 Volume:20 Page:
ISSN:1557-2064
Container-title:Sensing and Imaging
language:en
Short-container-title:Sens Imaging

Author:

Sunil Babu Melingi,Vijayalakshmi V.

Publisher

Springer Science and Business Media LLC

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://link.springer.com/content/pdf/10.1007/s11220-019-0230-6.pdf

Reference32 articles.

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3. Rekik, I., Allassonnière, S., Carpenter, T., & Wardlaw, J. (2013). Corrigendum to “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” [NeuroImage: Clinical 1 (2012) 164–178]. NeuroImage: Clinical, 2, 600. https://doi.org/10.1016/j.nicl.2013.04.013 .

4. Etgen, T., Steinich, I., & Gsottschneider, L. (2014). Thrombolysis for ischemic stroke in patients with brain tumors. Journal of Stroke and Cerebrovascular Diseases, 23(2), 361–366. https://doi.org/10.1016/j.jstrokecerebrovasdis.2013.05.004 .

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