Application of deep learning method on ischemic stroke lesion segmentation

Y Zhang, S Liu, C Li, J Wang - Journal of Shanghai Jiaotong University …, 2022 - Springer
Although deep learning methods have been widely applied in medical image lesion
segmentation, it is still challenging to apply it for segmenting ischemic stroke lesions, which …

Rethinking the dice loss for deep learning lesion segmentation in medical images

Y Zhang, S Liu, C Li, J Wang - Journal of Shanghai Jiaotong University …, 2021 - Springer
Deep learning is widely used for lesion segmentation in medical images due to its
breakthrough performance. Loss functions are critical in a deep learning pipeline, and they …

Deep multimodal learning from MRI and clinical data for early prediction of neurodevelopmental deficits in very preterm infants

L He, H Li, M Chen, J Wang, M Altaye… - Frontiers in …, 2021 - frontiersin.org
The prevalence of disabled survivors of prematurity has increased dramatically in the past 3
decades. These survivors, especially, very preterm infants (VPIs), born≤ 32 weeks …

Applications of deep learning to neurodevelopment in pediatric imaging: Achievements and challenges

M Hu, C Nardi, H Zhang, KK Ang - Applied Sciences, 2023 - mdpi.com
Deep learning has achieved remarkable progress, particularly in neuroimaging analysis.
Deep learning applications have also been extended from adult to pediatric medical images …

[HTML][HTML] Diffuse excessive high signal intensity in the preterm brain on advanced MRI represents widespread neuropathology

JE Kline, J Dudley, VSP Illapani, H Li, B Kline-Fath… - Neuroimage, 2022 - Elsevier
Preterm brains commonly exhibit elevated signal intensity in the white matter on T2-
weighted MRI at term-equivalent age. This signal, known as diffuse excessive high signal …

Novel diffuse white matter abnormality biomarker at term-equivalent age enhances prediction of long-term motor development in very preterm children

NA Parikh, K Harpster, L He, VSP Illapani, FC Khalid… - Scientific reports, 2020 - nature.com
Our objective was to evaluate the independent prognostic value of a novel MRI biomarker—
objectively diagnosed diffuse white matter abnormality volume (DWMA; diffuse excessive …

Automated detection of juvenile myoclonic epilepsy using CNN based transfer learning in diffusion MRI

X Si, X Zhang, Y Zhou, Y Sun, W Jin… - 2020 42nd Annual …, 2020 - ieeexplore.ieee.org
Epilepsy is one of the largest neurological diseases in the world, and juvenile myoclonic
epilepsy (JME) usually occurs in adolescents, giving patients tremendous burdens during …

Automatic segmentation of diffuse white matter abnormality on T2-weighted brain MR images using deep learning in very preterm infants

H Li, M Chen, J Wang, VSP Illapani… - Radiology: Artificial …, 2021 - pubs.rsna.org
About 50%–80% of very preterm infants (VPIs)(≤ 32 weeks gestational age) exhibit diffuse
white matter abnormality (DWMA) on their MR images at term-equivalent age. It remains …

Extracallosal structural connectivity is positively associated with language performance in well-performing children born extremely preterm

ME Barnes-Davis, BJ Williamson, SL Merhar… - Frontiers in …, 2022 - frontiersin.org
Children born extremely preterm (< 28 weeks gestation) are at risk for language delay or
disorders. Decreased structural connectivity in preterm children has been associated with …

Diffuse excessive high signal intensity on term equivalent MRI does not predict disability: a systematic review and meta-analysis

CP Rath, S Desai, SC Rao, S Patole - … of Disease in Childhood-Fetal and …, 2021 - fn.bmj.com
Objective To evaluate whether diffuse excessive high signal intensity (DEHSI) on term
equivalent age MRI (TEA-MRI) predicts disability in preterm infants. Design This is a …