Benchmark on automatic six-month-old infant brain segmentation algorithms: the iSeg-2017 challenge
Accurate segmentation of infant brain magnetic resonance (MR) images into white matter
(WM), gray matter (GM), and cerebrospinal fluid is an indispensable foundation for early …
(WM), gray matter (GM), and cerebrospinal fluid is an indispensable foundation for early …
Computational neuroanatomy of baby brains: A review
The first postnatal years are an exceptionally dynamic and critical period of structural,
functional and connectivity development of the human brain. The increasing availability of …
functional and connectivity development of the human brain. The increasing availability of …
Dual-sampling attention network for diagnosis of COVID-19 from community acquired pneumonia
The coronavirus disease (COVID-19) is rapidly spreading all over the world, and has
infected more than 1,436,000 people in more than 200 countries and territories as of April 9 …
infected more than 1,436,000 people in more than 200 countries and territories as of April 9 …
Hierarchical fully convolutional network for joint atrophy localization and Alzheimer's disease diagnosis using structural MRI
Structural magnetic resonance imaging (sMRI) has been widely used for computer-aided
diagnosis of neurodegenerative disorders, eg, Alzheimer's disease (AD), due to its …
diagnosis of neurodegenerative disorders, eg, Alzheimer's disease (AD), due to its …
Within-subject template estimation for unbiased longitudinal image analysis
Longitudinal image analysis has become increasingly important in clinical studies of normal
aging and neurodegenerative disorders. Furthermore, there is a growing appreciation of the …
aging and neurodegenerative disorders. Furthermore, there is a growing appreciation of the …
Latent representation learning for Alzheimer's disease diagnosis with incomplete multi-modality neuroimaging and genetic data
The fusion of complementary information contained in multi-modality data [eg, magnetic
resonance imaging (MRI), positron emission tomography (PET), and genetic data] has …
resonance imaging (MRI), positron emission tomography (PET), and genetic data] has …
Avoiding asymmetry-induced bias in longitudinal image processing
Longitudinal image processing procedures frequently transfer or pool information across
time within subject, with the dual goals of reducing the variability and increasing the …
time within subject, with the dual goals of reducing the variability and increasing the …
Adversarial learning for mono-or multi-modal registration
This paper introduces an unsupervised adversarial similarity network for image registration.
Unlike existing deep learning registration methods, our approach can train a deformable …
Unlike existing deep learning registration methods, our approach can train a deformable …
Longitudinal multiple sclerosis lesion segmentation: resource and challenge
In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion
segmentation challenge providing training and test data to registered participants. The …
segmentation challenge providing training and test data to registered participants. The …
DRAMMS: Deformable registration via attribute matching and mutual-saliency weighting
A general-purpose deformable registration algorithm referred to as “DRAMMS” is presented
in this paper. DRAMMS bridges the gap between the traditional voxel-wise methods and …
in this paper. DRAMMS bridges the gap between the traditional voxel-wise methods and …