Delineation of the ischemic stroke lesion based on watershed and relative fuzzy connectedness in brain MRI

2017 ◽  
Vol 56 (5) ◽  
pp. 795-807 ◽  
Author(s):  
Asit Subudhi ◽  
Subhranshu Jena ◽  
Sukanta Sabut
Keyword(s):  
Ischemic Stroke ◽  
Brain Mri ◽  
Fuzzy Connectedness ◽  
Stroke Lesion

U-Net Supported Segmentation of Ischemic-Stroke-Lesion from Brain MRI Slices

2021 ◽  
Author(s):  
Seifedine Kadry ◽  
Robertas Damasevicius ◽  
David Taniar ◽  
Venkatesan Rajinikanth ◽  
Isah A. Lawal
Keyword(s):  
Ischemic Stroke ◽  
Brain Mri ◽  
Stroke Lesion

scholarly journals Stroke Lesion Detection and Analysis in MRI Images Based on Deep Learning

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Shujun Zhang ◽  
Shuhao Xu ◽  
Liwei Tan ◽  
Hongyan Wang ◽  
Jianli Meng
Keyword(s):  
Ischemic Stroke ◽  
Deep Learning ◽  
Deep Neural Networks ◽  
Brain Mri ◽  
Lesion Detection ◽  
Learning Ability ◽  
Massive Data ◽  
Stroke Patients ◽  
Stroke Lesion ◽  
Assisted Diagnosis

Stroke is a kind of cerebrovascular disease that heavily damages people’s life and health. The quantitative analysis of brain MRI images plays an important role in the diagnosis and treatment of stroke. Deep neural networks with massive data learning ability supply a powerful tool for lesion detection. In order to study the property of the stroke lesions and complete intelligent automatic detection, we collaborated with two authoritative hospitals and collected 5,668 brain MRI images of 300 ischemic stroke patients. All the lesion regions in the images were accurately labeled by professional doctors to ensure the authority and effectiveness of the data. Three categories of deep learning object detection networks including Faster R-CNN, YOLOV3, and SSD are applied to implement automatic lesion detection with the best precision of 89.77%. Meanwhile, statistical analysis of the locations, shapes of the lesions, and possible related diseases is conducted with valid conclusions. The research contributes to the intelligent assisted diagnosis and prevention and treatment of ischemic stroke.

scholarly journals Deep Learning Framework to Detect Ischemic Stroke Lesion in Brain MRI Slices of Flair/DW/T1 Modalities

Symmetry ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2080
Author(s):  
Venkatesan Rajinikanth ◽  
Shabnam Mohamed Aslam ◽  
Seifedine Kadry
Keyword(s):  
Feature Extraction ◽  
Ischemic Stroke ◽  
Deep Learning ◽  
Brain Mri ◽  
Brain Abnormality ◽  
Deep Feature ◽  
Feature Based ◽  
Stroke Lesion ◽  
Binary Classifiers ◽  
Feature Based Classification

Ischemic stroke lesion (ISL) is a brain abnormality. Studies proved that early detection and treatment could reduce the disease impact. This research aimed to develop a deep learning (DL) framework to detect the ISL in multi-modality magnetic resonance image (MRI) slices. It proposed a convolutional neural network (CNN)-supported segmentation and classification to execute a consistent disease detection framework. The developed framework consisted of the following phases; (i) visual geometry group (VGG) developed VGG16 scheme supported SegNet (VGG-SegNet)-based ISL mining, (ii) handcrafted feature extraction, (iii) deep feature extraction using the chosen DL scheme, (iv) feature ranking and serial feature concatenation, and (v) classification using binary classifiers. Fivefold cross-validation was employed in this work, and the best feature was selected as the final result. The attained results were separately examined for (i) segmentation; (ii) deep-feature-based classification, and (iii) concatenated feature-based classification. The experimental investigation is presented using the Ischemic Stroke Lesion Segmentation (ISLES2015) database. The attained result confirms that the proposed ISL detection framework gives better segmentation and classification results. The VGG16 scheme helped to obtain a better result with deep features (accuracy > 97%) and concatenated features (accuracy > 98%).

scholarly journals Pure Motor Stroke Secondary to Cerebral Infarction of Recurrent Artery of Heubner after Mild Head Trauma: A Case Report

2016 ◽  
Vol 4 (1) ◽  
pp. 139-141
Author(s):  
Ali Yilmaz ◽  
Zahir Kizilay ◽  
Ayca Ozkul ◽  
Bayram Çirak
Keyword(s):  
Ischemic Stroke ◽  
Head Trauma ◽  
Distal Part ◽  
Brain Mri ◽  
Artery Occlusion ◽  
Acute Ischemia ◽  
Post Traumatic ◽  
The Brain ◽  
Perforating Arteries ◽  
Pure Motor

BACKGROUND: The recurrent Heubner's artery is the distal part of the medial striate artery. Occlusion of the recurrent artery of Heubner, classically contralateral hemiparesis with fasciobrachiocrural predominance, is attributed to the occlusion of the recurrent artery of Heubner and is widely known as a stroke syndrome in adults. However, isolated occlusion of the deep perforating arteries following mild head trauma also occurs extremely rarely in childhood.CASE REPORT: Here we report the case of an 11-year-old boy with pure motor stroke. The brain MRI showed an acute ischemia in the recurrent artery of Heubner supply area following mild head trauma. His fasciobrachial hemiparesis and dysarthria were thought to be secondary to the stretching of deep perforating arteries leading to occlusion of the recurrent artery of Heubner.CONCLUSION: Post-traumatic pure motor ischemic stroke can be secondary to stretching of the deep perforating arteries especially in childhood.

scholarly journals Correction: Classifiers for Ischemic Stroke Lesion Segmentation: A Comparison Study

PLoS ONE ◽  
2016 ◽  
Vol 11 (2) ◽  
pp. e0149828 ◽  
Author(s):  
Oskar Maier ◽  
Christoph Schröder ◽  
Nils Daniel Forkert ◽  
Thomas Martinetz ◽  
Heinz Handels
Keyword(s):  
Ischemic Stroke ◽  
Comparison Study ◽  
Lesion Segmentation ◽  
Stroke Lesion

Abstract TP417: An Autoregulation-Derived Prediction Model for Midline Shift After Ischemic Stroke

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Andrew Silverman ◽  
Anson Wang ◽  
Sreeja Kodali ◽  
Sumita Strander ◽  
Alexandra Kimmel ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Predictive Model ◽  
Infarct Volume ◽  
Classification Tree ◽  
Brain Mri ◽  
Projection Pursuit ◽  
Midline Shift ◽  
Vessel Occlusion ◽  
Patient Disposition ◽  
Hemodynamic Variables

Introduction: Identification of patients likely to develop midline shift (MLS) after large-vessel occlusion (LVO) stroke is essential for appropriate triage and patient disposition. Studies have identified clinical and radiographic predictors of MLS, but with limited accuracy. Using an innovative assessment of cerebral autoregulation, we sought to develop an accurate predictive model for MLS. Methods: We prospectively enrolled 73 patients with LVO stroke. Beat-by-beat cerebral blood flow (transcranial Doppler) and arterial pressure (arterial catheter or finger photoplethysmography) were recorded within 24 hours of the stroke, and a 24-hour brain MRI was obtained to determine infarct volume and MLS. Autoregulatory function was quantified from pressure-flow relation via projection pursuit regression (PPR), allowing for characterization of 5 hemodynamic markers (Figure 1A). We assessed the predictive relation of autoregulatory capacity and radiological and clinical variables to MLS using recursive classification tree models. Results: PPR successfully quantified autoregulatory function in 50/73 (68.5%) patients within 24 hours of LVO ischemic stroke (age 63.9±13.6, 66% F, NIHSS 15.8±6.7). Of these 50 patients, most (78%) underwent endovascular therapy. Thirteen (26%) experienced 24-h MLS; in these patients, infarct volumes were larger (140.2 vs. 48.6 mL, P<0.001 ), and ipsilateral (but not contralateral) falling slopes were steeper (1.1 vs. 0.7 cm·s -1 ·mmHg -1 , P=0.001 ). Among all clinical, demographic, and hemodynamic variables, only two (infarct volume, ipsilateral falling slope) significantly contributed to prediction of MLS (accuracy 94%; Figure 1B). Conclusions: This predictive model of MLS wields translatable potential for triaging level of care in patients suffering from LVO ischemic stroke, but further research, including optimization of the PPR algorithm as well as prospective use of the predictive model, is needed.

Abstract WP190: Clinical Features of Sarcoid Patients With Ischemic Stroke

Stroke ◽  
2016 ◽  
Vol 47 (suppl_1) ◽  
Author(s):  
Ahmed Z Obeidat ◽  
Heidi Sucharew ◽  
Charles J Moomaw ◽  
Dawn O Kleindorfer ◽  
Brett M Kissela ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Current Knowledge ◽  
Case Reports ◽  
Brain Mri ◽  
Sporadic Case ◽  
Prior History ◽  
Stroke Patients ◽  
Stroke Subtype ◽  
Stroke Event ◽  
History Of

Background: Current knowledge on ischemic stroke in sarcoid patients stems from sporadic case reports. The mechanism is thought to be related to granulomatous involvement of brain vasculature. However, clinical, demographic, and radiographic features of sarcoid patients with ischemic stroke are lacking. If sarcoid patients are at higher risk for ischemic stroke event, we hypothesized that the risk factors for ischemic stroke and stroke subtype distribution would differ between sarcoid and non-sarcoid ischemic stroke patients. Methods: Cases of ischemic stroke were identified for the years 2005 and 2010 from the population-based Greater Cincinnati/Northern Kentucky Stroke Study (population 1.3 million). Ischemic stroke cases were physician study confirmed and patients with a history of sarcoid were identified through medical chart review. Clinical variables were compared between stroke patients with history of sarcoid and those with no prior sarcoid history. Results: A total of 4258 cases of ischemic stroke were identified; of them, only 18 had prior diagnosis of sarcoid (0.04%). Brain MRI showed diffusion restriction in 14 out of 15 (93%) MRIs performed in sarcoid patients. The table presents risk factor and subtype data on sarcoid patients compared with non-sarcoid patients. Conclusions: We identified only a few cases of prior sarcoid history in our two-year ascertainment of ischemic stroke patients in our population. In comparison with stroke patients with no prior history of sarcoid, the sarcoid patients tended to be of younger age at presentation, female, have a history of diabetes and hyperlipidemia, and more likely of African descent, perhaps related to the diagnosis of sarcoid itself. We were unable to detect differences in stroke subtype distributions between sarcoid and non-sarcoid ischemic stroke patients.

P3712The omega-3 fatty acid eicosapentaenoic acid (EPA) is inversely associated with ischemic brain infarcts in elderly patients with atrial fibrillation

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
M F Reiner ◽  
P Baumgartner ◽  
A Wiencierz ◽  
S Aeschbacher ◽  
N Rodondi ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Ischemic Stroke ◽  
Elderly Patients ◽  
Eicosapentaenoic Acid ◽  
Brain Mri ◽  
Omega 3 ◽  
Total N ◽  
Stroke Incidence ◽  
Ischemic Brain ◽  
Brain Infarcts

Abstract Background The association of individual omega-3 fatty acids (n-3 FAs) with ischemic stroke remains unclear. Experimental data strongly suggest that n-3 FAs reduce ischemic stroke due to their anti-thrombotic and anti-inflammatory properties. Yet, recent clinical trials yielded mixed results. While marine n-3 FA supplementation (1g/day) did not reduce stroke, icosapent ethyl, a purified eicosapentaenoic acid (EPA) ethyl ester (4g/day), significantly reduced stroke incidence in patients at high cardiovascular risk. In the current study, we examined the association of fish-derived EPA, docosapentaenoic acid (DPA), docosahexaenoic acid (DHA) and the plant-derived alpha-linolenic acid (ALA) with the prevalence of ischemic brain infarcts in elderly patients with atrial fibrillation. Methods In this cross-sectional analysis of the Swiss atrial fibrillation (swissAF) cohort study, we determined baseline whole blood n-3 FAs by gas chromatography according to the HS-Omega-3 Index methodology in 1665 patients aged ≥65 years with atrial fibrillation. Large non-cortical and cortical infarcts (LNCCI) were assessed by brain MRI. Total and individual n-3 FAs were correlated with the prevalence of LNCCI in a logit model with continuous factors. Analyses were adjusted for sex, age, body mass index, smoking, alcohol intake, family history of cardiovascular disease and atrial fibrillation, physical activity, hypertension, diabetes, chronic kidney disease, prior stroke, prior transient ischemic attack, aspirin, anticoagulation and type of atrial fibrillation. Results A total of 373 patients with LNCCI (22.4%) were identified. After adjustment, lower risk of LNCCI was associated with higher EPA (odds ratio [OR] 0.50 per increase of one percentage point EPA, 95% confidence interval [CI] 0.28–0.88) and a higher risk was detected with DPA (OR 2.39, 95% CI 1.43–4.01). No statistically significant association was detected with DHA (OR 1.13, 95% CI 0.94–1.35), ALA (OR 0.83, 95% CI 0.23–2.95) or total n-3 FAs (OR 1.03, 95% CI 0.92–1.16). Conclusions Higher levels of EPA are associated with a lower prevalence of ischemic infarcts in aged patients with atrial fibrillation. Unexpectedly, DPA shows a direct correlation with ischemic infarcts. This study demonstrates that individual n-3 FAs may differentially affect stroke risk and that supplementation of EPA may be an interesting strategy to prevent ischemic stroke in atrial fibrillation patients. Acknowledgement/Funding Swiss National Science Foundation

Sign in / Sign up

Export Citation Format

Share Document