ArticleMedical image analysis2014
Automated detection of brain abnormalities in neonatal hypoxia ischemic injury from MR images.
Article in Medical image analysis, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 40 citations in OpenAlex.
- Protocol to optimize the Rice-Vannucci rat pup model of perinatal asphyxia to ensure predictable hypoxic-ischemic cerebral lesions.STAR protocols · 2024Article
- Deep learning-based automated lesion segmentation on mouse stroke magnetic resonance images.Scientific reports · 2023Article
- A Review on Computer Aided Diagnosis of Acute Brain Stroke.Sensors (Basel, Switzerland) · 2021Review
- Acute intranasal osteopontin treatment in male rats following TBI increases the number of activated microglia but does not alter lesion characteristics.Journal of neuroscience research · 2020Article
- CX3CR1-CCR2-dependent monocyte-microglial signaling modulates neurovascular leakage and acute injury in a mouse model of childhood stroke.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2019Article
- Male and Female Mice Exhibit Divergent Responses of the Cortical Vasculature to Traumatic Brain Injury.Journal of neurotrauma · 2018Article
- ISLES 2015 - A public evaluation benchmark for ischemic stroke lesion segmentation from multispectral MRI.Medical image analysis · 2017Article
- Automated Ischemic Lesion Segmentation in MRI Mouse Brain Data after Transient Middle Cerebral Artery Occlusion.Frontiers in neuroinformatics · 2017Article
- Automatic quantification of ischemic injury on diffusion-weighted MRI of neonatal hypoxic ischemic encephalopathy.NeuroImage. Clinical · 2017Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
We compared the efficacy of three automated brain injury detection methods, namely symmetry-integrated region growing (SIRG), hierarchical region splitting (HRS) and modified watershed segmentation (MWS) in human and animal magnetic resonance imaging (MRI) datasets for the detection of hypoxic ischemic injuries (HIIs). Diffusion weighted imaging (DWI, 1.5T) data from neonatal arterial ischemic stroke (AIS) patients, as well as T2-weighted imaging (T2WI, 11.7T, 4.7T) at seven different time-points (1, 4, 7, 10, 17, 24 and 31 days post HII) in rat-pup model of hypoxic ischemic injury were used to assess the temporal efficacy of our computational approaches. Sensitivity, specificity, and similarity were used as performance metrics based on manual ('gold standard') injury detection to quantify comparisons. When compared to the manual gold standard, automated injury location results from SIRG performed the best in 62% of the data, while 29% for HRS and 9% for MWS. Injury severity detection revealed that SIRG performed the best in 67% cases while 33% for HRS. Prior information is required by HRS and MWS, but not by SIRG. However, SIRG is sensitive to parameter-tuning, while HRS and MWS are not. Among these methods, SIRG performs the best in detecting lesion volumes; HRS is the most robust, while MWS lags behind in both respects.
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