Computer-assisted delineation of cerebral infarct from diffusion-weighted MRI using Gaussian mixture model
Sign Up to like & getrecommendations! Published in 2017 at "International Journal of Computer Assisted Radiology and Surgery"
DOI: 10.1007/s11548-017-1520-x
Abstract: PurposeDiffusion-weighted imaging (DWI) is a widely used medical imaging modality for diagnosis and monitoring of cerebral stroke. The identification of exact location of stroke lesion helps in perceiving its characteristics, an essential part of diagnosis… read more here.
Keywords: mixture model; methodology; stroke lesion; computer assisted ... See more keywords
Acute ischemic stroke lesion core segmentation in CT perfusion images using fully convolutional neural networks
Sign Up to like & getrecommendations! Published in 2019 at "Computers in biology and medicine"
DOI: 10.1016/j.compbiomed.2019.103487
Abstract: The use of Computed Tomography (CT) imaging for patients with stroke symptoms is an essential step for triaging and diagnosis in many hospitals. However, the subtle expression of ischemia in acute CT images has made… read more here.
Keywords: lesion core; core segmentation; lesion; stroke lesion ... See more keywords
Automated stroke lesion segmentation in non-contrast CT scans using dense multi-path contextual generative adversarial network.
Sign Up to like & getrecommendations! Published in 2020 at "Physics in medicine and biology"
DOI: 10.1088/1361-6560/aba166
Abstract: BACKGROUND AND OBJECTIVE Stroke lesion volume is a key radiologic measurement in assessing prognosis of acute ischemic stroke (AIS) patients. The aim of this paper is to develop an automated segmentation method for accurately segmenting… read more here.
Keywords: network; stroke lesion; segmentation; dense multi ... See more keywords
MDAN: Mirror Difference Aware Network for Brain Stroke Lesion Segmentation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2021.3113460
Abstract: Brain stroke lesion segmentation is of great importance for stroke rehabilitation neuroimaging analysis. Due to the large variance of stroke lesion shapes and similarities of tissue intensity distribution, it remains a challenging task. To help… read more here.
Keywords: lesion segmentation; brain; difference; stroke lesion ... See more keywords
Simulated Quantum Mechanics-Based Joint Learning Network for Stroke Lesion Segmentation and TICI Grading.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE journal of biomedical and health informatics"
DOI: 10.1109/jbhi.2023.3270861
Abstract: Segmenting stroke lesions and assessing the thrombolysis in cerebral infarction (TICI) grade are two important but challenging prerequisites for an auxiliary diagnosis of the stroke. However, most previous studies have focused only on a single… read more here.
Keywords: network; stroke lesion; segmentation; mechanics ... See more keywords
Stroke Lesion Outcome Prediction Based on MRI Imaging Combined With Clinical Information
Sign Up to like & getrecommendations! Published in 2018 at "Frontiers in Neurology"
DOI: 10.3389/fneur.2018.01060
Abstract: In developed countries, the second leading cause of death is stroke, which has the ischemic stroke as the most common type. The preferred diagnosis procedure involves the acquisition of multi-modal Magnetic Resonance Imaging. Besides detecting… read more here.
Keywords: outcome prediction; lesion outcome; clinical information; stroke lesion ... See more keywords
Deep Learning Framework to Detect Ischemic Stroke Lesion in Brain MRI Slices of Flair/DW/T1 Modalities
Sign Up to like & getrecommendations! Published in 2021 at "Symmetry"
DOI: 10.3390/sym13112080
Abstract: 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… read more here.
Keywords: ischemic stroke; feature; stroke lesion; framework ... See more keywords