[HTML][HTML] Deep learning based synthesis of MRI, CT and PET: Review and analysis
Medical image synthesis represents a critical area of research in clinical decision-making,
aiming to overcome the challenges associated with acquiring multiple image modalities for …
aiming to overcome the challenges associated with acquiring multiple image modalities for …
iBEAT V2. 0: a multisite-applicable, deep learning-based pipeline for infant cerebral cortical surface reconstruction
The human cerebral cortex undergoes dramatic and critical development during early
postnatal stages. Benefiting from advances in neuroimaging, many infant brain magnetic …
postnatal stages. Benefiting from advances in neuroimaging, many infant brain magnetic …
Deep learning for brain MRI segmentation: state of the art and future directions
Quantitative analysis of brain MRI is routine for many neurological diseases and conditions
and relies on accurate segmentation of structures of interest. Deep learning-based …
and relies on accurate segmentation of structures of interest. Deep learning-based …
Deep learning in medical image analysis
This review covers computer-assisted analysis of images in the field of medical imaging.
Recent advances in machine learning, especially with regard to deep learning, are hel** …
Recent advances in machine learning, especially with regard to deep learning, are hel** …
VoxResNet: Deep voxelwise residual networks for brain segmentation from 3D MR images
Segmentation of key brain tissues from 3D medical images is of great significance for brain
disease diagnosis, progression assessment and monitoring of neurologic conditions. While …
disease diagnosis, progression assessment and monitoring of neurologic conditions. While …
The present and future of deep learning in radiology
Abstract The advent of Deep Learning (DL) is poised to dramatically change the delivery of
healthcare in the near future. Not only has DL profoundly affected the healthcare industry it …
healthcare in the near future. Not only has DL profoundly affected the healthcare industry it …
Automatic segmentation of MR brain images with a convolutional neural network
Automatic segmentation in MR brain images is important for quantitative analysis in large-
scale studies with images acquired at all ages. This paper presents a method for the …
scale studies with images acquired at all ages. This paper presents a method for the …
The develo** human connectome project: A minimal processing pipeline for neonatal cortical surface reconstruction
Abstract The Develo** Human Connectome Project (dHCP) seeks to create the first 4-
dimensional connectome of early life. Understanding this connectome in detail may provide …
dimensional connectome of early life. Understanding this connectome in detail may provide …
Deeply supervised 3D fully convolutional networks with group dilated convolution for automatic MRI prostate segmentation
Purpose Reliable automated segmentation of the prostate is indispensable for image‐
guided prostate interventions. However, the segmentation task is challenging due to …
guided prostate interventions. However, the segmentation task is challenging due to …
Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach
In this paper, we present a novel automated method for White Matter (WM) lesion
segmentation of Multiple Sclerosis (MS) patient images. Our approach is based on a …
segmentation of Multiple Sclerosis (MS) patient images. Our approach is based on a …