What is he best known for?
The fields of study he is best known for:
- Magnetic resonance imaging
- Internal medicine
- Artificial intelligence
Weili Lin mostly deals with Magnetic resonance imaging, Neuroscience, White matter, Brain mapping and Nuclear medicine.
His Magnetic resonance imaging study integrates concerns from other disciplines, such as Histopathology, Nuclear magnetic resonance, Computer vision and Artificial intelligence.
His Pattern recognition research extends to the thematically linked field of Artificial intelligence.
Weili Lin combines subjects such as Diffusion MRI, Physiology and Subgroup analysis with his study of White matter.
In his study, Developmental psychology is strongly linked to Resting state fMRI, which falls under the umbrella field of Brain mapping.
His Nuclear medicine research also works with subjects such as
- Pathology, which have a strong connection to Ischemia, Vascular disease, Cardiology, Voxel and Internal medicine,
- Central nervous system disease and related Vein.
His most cited work include:
- A Structural MRI Study of Human Brain Development from Birth to 2 Years (659 citations)
- Deep convolutional neural networks for multi-modality isointense infant brain image segmentation. (491 citations)
- Evidence on the emergence of the brain's default network from 2-week-old to 2-year-old healthy pediatric subjects (385 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Artificial intelligence, Magnetic resonance imaging, Pattern recognition, Neuroscience and White matter.
His research integrates issues of Neuroimaging and Computer vision in his study of Artificial intelligence.
His study in Magnetic resonance imaging is interdisciplinary in nature, drawing from both Positron emission tomography, Nuclear medicine, Pathology, Stroke and Nuclear magnetic resonance.
His Nuclear medicine research incorporates elements of Radiology and Cerebral blood flow.
The study incorporates disciplines such as Surface, Cortical surface and Residual in addition to Pattern recognition.
He interconnects Diffusion MRI and Brain mapping in the investigation of issues within White matter.
He most often published in these fields:
- Artificial intelligence (35.89%)
- Magnetic resonance imaging (30.25%)
- Pattern recognition (20.54%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (35.89%)
- Pattern recognition (20.54%)
- Deep learning (7.67%)
In recent papers he was focusing on the following fields of study:
Weili Lin mainly focuses on Artificial intelligence, Pattern recognition, Deep learning, Neuroscience and Brain development.
His Artificial intelligence study incorporates themes from White matter, Magnetic resonance imaging, Machine learning and Neuroimaging.
Weili Lin has researched White matter in several fields, including Perivascular space and Brain segmentation.
His work deals with themes such as Image processing, Image and Medical imaging, which intersect with Magnetic resonance imaging.
He studies Segmentation, a branch of Pattern recognition.
His biological study spans a wide range of topics, including Cortex and Brain tissue.
Between 2018 and 2021, his most popular works were:
- The UNC/UMN Baby Connectome Project (BCP): An overview of the study design and protocol development. (93 citations)
- 3-D Fully Convolutional Networks for Multimodal Isointense Infant Brain Image Segmentation (72 citations)
- Benchmark on Automatic Six-Month-Old Infant Brain Segmentation Algorithms: The iSeg-2017 Challenge (63 citations)
In his most recent research, the most cited papers focused on:
- Magnetic resonance imaging
- Internal medicine
- Artificial intelligence
His primary areas of study are Artificial intelligence, Pattern recognition, Neuroscience, Magnetic resonance imaging and Deep learning.
His Pattern recognition research is multidisciplinary, incorporating elements of Image resolution, Image and Residual.
His research on Magnetic resonance imaging focuses in particular on White matter.
His White matter research incorporates themes from Relaxation, Imaging phantom, Nuclear medicine and Brain tissue.
His Deep learning research includes elements of Channel, Template matching and Convolutional neural network.
Weili Lin has included themes like Hippocampal formation, Embedding and Contrast in his Segmentation study.
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