What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Surgery
- Computer vision
His primary areas of study are Artificial intelligence, Segmentation, Computer vision, Orthopedic surgery and Surgery.
As part of his studies on Artificial intelligence, he often connects relevant areas like Algorithm.
His work carried out in the field of Segmentation brings together such families of science as Deep learning and Hausdorff distance.
His Computer vision study integrates concerns from other disciplines, such as Outlier and Mr images.
His research investigates the connection between Orthopedic surgery and topics such as Acetabulum that intersect with issues in Pelvis and Radiography.
His studies in Surgery integrate themes in fields like Sagittal plane and Navigation system.
His most cited work include:
- Tilt and rotation correction of acetabular version on pelvic radiographs. (241 citations)
- Crowd Counting with Deep Negative Correlation Learning (170 citations)
- What Are the Radiographic Reference Values for Acetabular Under- and Overcoverage? (141 citations)
What are the main themes of his work throughout his whole career to date?
Guoyan Zheng spends much of his time researching Artificial intelligence, Computer vision, Segmentation, Surgery and Radiography.
His work in Artificial intelligence is not limited to one particular discipline; it also encompasses Pattern recognition.
Guoyan Zheng works mostly in the field of Computer vision, limiting it down to topics relating to Imaging phantom and, in certain cases, Similarity measure.
He has included themes like Random forest, Convolutional neural network, Image and Mr images in his Segmentation study.
He has researched Surgery in several fields, including Nuclear medicine and Navigation system.
The concepts of his Radiography study are interwoven with issues in Orthodontics, Total hip arthroplasty and Pelvis.
He most often published in these fields:
- Artificial intelligence (54.93%)
- Computer vision (41.79%)
- Segmentation (22.99%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (54.93%)
- Segmentation (22.99%)
- Deep learning (5.67%)
In recent papers he was focusing on the following fields of study:
His main research concerns Artificial intelligence, Segmentation, Deep learning, Computer vision and Pattern recognition.
Guoyan Zheng has included themes like Lumbar and Nonlinear regression in his Artificial intelligence study.
His study in the field of Sørensen–Dice coefficient is also linked to topics like Context.
His Deep learning study combines topics in areas such as Algorithm and Big data.
His Computer vision study often links to related topics such as Intervertebral disc.
His Pattern recognition research incorporates themes from Image, Image translation, Hyperintensity and Test set.
Between 2017 and 2021, his most popular works were:
- Crowd Counting with Deep Negative Correlation Learning (170 citations)
- Why rankings of biomedical image analysis competitions should be interpreted with care (87 citations)
- Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge (80 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Surgery
- Statistics
His primary scientific interests are in Segmentation, Artificial intelligence, Pattern recognition, Deep learning and Femoroacetabular impingement.
In the field of Segmentation, his study on Sørensen–Dice coefficient overlaps with subjects such as Fully automatic.
His Voxel study in the realm of Artificial intelligence connects with subjects such as Negative correlation.
His work on Image segmentation as part of general Pattern recognition study is frequently linked to Context, therefore connecting diverse disciplines of science.
His Deep learning research includes elements of Algorithm, Nonlinear regression and Regression.
Guoyan Zheng has researched Femoroacetabular impingement in several fields, including 3D reconstruction, Femur, Avascular necrosis, Hip arthroscopy and Random forest.
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