Editorial for “Fully Automated MRI Segmentation and Volumetric Measurement of Intracranial Meningioma Using Deep Learning”
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Magnetic Resonance Imaging"
DOI: 10.1002/jmri.28329
Abstract: T his study 1 applied nnU-Net, developed by Isensee et al, 2 to as many as 659 meningioma patient images in total after contrast enhancement for automatic segmentation. Both training and validation data images were… read more here.
Keywords: editorial fully; fully automated; segmentation volumetric; automated mri ... See more keywords
Efficient multi-kernel DCNN with pixel dropout for stroke MRI segmentation
Sign Up to like & getrecommendations! Published in 2019 at "Neurocomputing"
DOI: 10.1016/j.neucom.2019.03.049
Abstract: Abstract As manual delineation of lesions in medical image is a very tedious and time consuming process, accurate and automatic segmentation of medical images can assist diagnosis and treatment. In this study, we propose a… read more here.
Keywords: efficient multi; mri segmentation; kernel dcnn; segmentation ... See more keywords
A squeeze U-SegNet architecture based on residual convolution for brain MRI segmentation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3175188
Abstract: This paper proposes an improved brain magnetic resonance imaging (MRI) segmentation model by integrating U-SegNet with fire modules and residual convolutions to segment brain tissues in MRI. In the proposed encoder-decoder method, the residual connections… read more here.
Keywords: brain mri; brain; segmentation; architecture ... See more keywords
TW-Net: Transformer Weighted Network for Neonatal Brain MRI Segmentation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2022.3225475
Abstract: Accurate neonatal brain MRI segmentation is valuable for investigating brain growth patterns and tracking the progression of neurodevelopmental disorders. However, it is a challenging task to use intensity-based methods to segment neonatal brain structures because… read more here.
Keywords: brain mri; brain; neonatal brain; mri segmentation ... See more keywords
White Matter Hyperintensities and Poststroke Apathy: A Fully Automated MRI Segmentation Study.
Sign Up to like & getrecommendations! Published in 2022 at "Cerebrovascular diseases"
DOI: 10.1159/000526939
Abstract: INTRODUCTION Poststroke apathy (PSA) is a common neuropsychiatric disorder that may affect up to 30% of stroke patients. Despite the difficulties of investigating this condition (overlapping with depression, heterogeneity of diagnostic criteria, a small number… read more here.
Keywords: matter; poststroke apathy; white matter; mri segmentation ... See more keywords
nn-TransUNet: An Automatic Deep Learning Pipeline for Heart MRI Segmentation
Sign Up to like & getrecommendations! Published in 2022 at "Life"
DOI: 10.3390/life12101570
Abstract: Cardiovascular disease (CVD) is a disease with high mortality in modern times. The segmentation task for MRI to extract the related organs for CVD is essential for diagnosis. Currently, a large number of deep learning… read more here.
Keywords: segmentation; deep learning; mri segmentation; transunet ... See more keywords