Anatomy-Guided Convolutional Neural Network for Motion Correction in Fetal Brain MRI

Pei, Yuchen; Wang, Lisheng; Zhao, Fenqiang; Zhong, Tao; Liao, Lufan; Shen, Dinggang; Li, Gang

doi:10.1007/978-3-030-59861-7_39

“…In recent years, automatic methods based on deep learning methods (DLMs) have been used to rapidly and objectively evaluate the image quality compared with conventional visual inspection. [7][8][9] In this issue of the Journal of Magnetic Resonance Imaging, Largent et al proposed, assessed and compared three multi-instance deep learning methods (MI DLMs), MI count-based DLM (MI-CB-DLM), MI vote-based DLM (MI-VB-DLM), and MI feature embedding DLM (MI-FE-DLM), for automatic assessment of fetal brain MR image quality after three-dimensional reconstruction as well as to explore the influence of fetal gestational age (GA) on the performance of the MI DLMs. 7 Two hundred and seventy-one MR scans were performed for 211 fetuses and acquired in orthorhombic (axial, sagittal, and coronal) planes using a T2-weighted two-dimensional single-shot fast spin-echo sequence.…”

mentioning

confidence: 99%

“…Although those sequences and reconstruction algorithms have improved the overall image quality, it still needs to visually assess the images, which is carried out within the imaging phase and after data reconstruction. In recent years, automatic methods based on deep learning methods (DLMs) have been used to rapidly and objectively evaluate the image quality compared with conventional visual inspection 7–9 …”

mentioning

confidence: 99%

Editorial for “Image Quality Assessment of Fetal Brain MRI Using Multi‐Instance Deep Learning Methods”

Chen

¹

2021

Magnetic Resonance Imaging

2

0

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Exaggerated anticipatory anxiety is common in social anxiety disorder (SAD). Neuroimaging studies have revealed altered neural activity in response to social stimuli in SAD, but fewer studies have examined neural activity during anticipation of feared social stimuli in SAD. The current study examined the time course and magnitude of activity in threat processing brain regions during speech anticipation in socially anxious individuals and healthy controls (HC). Method Participants (SAD n = 58; HC n = 16) underwent functional magnetic resonance imaging (fMRI) during which they completed a 90s control anticipation task and 90s speech anticipation task.

SVoRT: Iterative Transformer for Slice-to-Volume Registration in Fetal Brain MRI

Xu

¹

,

Moyer²,

Grant

³

et al. 2022

Lecture Notes in Computer Science

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Exaggerated anticipatory anxiety is common in social anxiety disorder (SAD). Neuroimaging studies have revealed altered neural activity in response to social stimuli in SAD, but fewer studies have examined neural activity during anticipation of feared social stimuli in SAD. The current study examined the time course and magnitude of activity in threat processing brain regions during speech anticipation in socially anxious individuals and healthy controls (HC). Method Participants (SAD n = 58; HC n = 16) underwent functional magnetic resonance imaging (fMRI) during which they completed a 90s control anticipation task and 90s speech anticipation task.

Advancements in MRI application in the morphological development of fetal cerebral venous system: a review

Zhao

¹

,

Cao

²

,

Yi

³

et al. 2025

Childs Nerv Syst

0

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Exaggerated anticipatory anxiety is common in social anxiety disorder (SAD). Neuroimaging studies have revealed altered neural activity in response to social stimuli in SAD, but fewer studies have examined neural activity during anticipation of feared social stimuli in SAD. The current study examined the time course and magnitude of activity in threat processing brain regions during speech anticipation in socially anxious individuals and healthy controls (HC). Method Participants (SAD n = 58; HC n = 16) underwent functional magnetic resonance imaging (fMRI) during which they completed a 90s control anticipation task and 90s speech anticipation task.

Anatomy-Guided Convolutional Neural Network for Motion Correction in Fetal Brain MRI

Cited by 6 publications

References 19 publications

Editorial for “Image Quality Assessment of Fetal Brain MRI Using Multi‐Instance Deep Learning Methods”

Editorial for “Image Quality Assessment of Fetal Brain MRI Using Multi‐Instance Deep Learning Methods”

SVoRT: Iterative Transformer for Slice-to-Volume Registration in Fetal Brain MRI

Advancements in MRI application in the morphological development of fetal cerebral venous system: a review

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