What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Internal medicine
- Statistics
His main research concerns Image registration, Artificial intelligence, Computer vision, Segmentation and Magnetic resonance imaging.
His biological study spans a wide range of topics, including Stochastic gradient descent, Medical imaging, Image processing, Medical physics and Software.
Stefan Klein has included themes like Machine learning and Pattern recognition in his Artificial intelligence study.
His Computer vision study integrates concerns from other disciplines, such as Interface and Diffusion MRI.
His Segmentation study combines topics in areas such as White matter and Neuroimaging.
His study in Magnetic resonance imaging is interdisciplinary in nature, drawing from both Nuclear medicine, Pathology, Region of interest, Cartilage and Cerebral blood flow.
His most cited work include:
- elastix : A Toolbox for Intensity-Based Medical Image Registration (2313 citations)
- Evaluation of Optimization Methods for Nonrigid Medical Image Registration Using Mutual Information and B-Splines (340 citations)
- Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge (330 citations)
What are the main themes of his work throughout his whole career to date?
Stefan Klein focuses on Artificial intelligence, Image registration, Computer vision, Magnetic resonance imaging and Segmentation.
His Artificial intelligence research is multidisciplinary, relying on both Machine learning and Pattern recognition.
His work carried out in the field of Image registration brings together such families of science as Stochastic gradient descent, Medical imaging, Image processing, Algorithm and Principal component analysis.
He has researched Computer vision in several fields, including Gradient descent, Carotid arteries and Ultrasound.
He focuses mostly in the field of Magnetic resonance imaging, narrowing it down to topics relating to Nuclear medicine and, in certain cases, Reproducibility.
His Segmentation study incorporates themes from Ground truth, Convolutional neural network and Atlas.
He most often published in these fields:
- Artificial intelligence (42.86%)
- Image registration (25.44%)
- Computer vision (25.09%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (42.86%)
- Segmentation (17.42%)
- Pattern recognition (14.29%)
In recent papers he was focusing on the following fields of study:
Stefan Klein mainly focuses on Artificial intelligence, Segmentation, Pattern recognition, Radiomics and Machine learning.
His research in Artificial intelligence intersects with topics in Consistency, Neuroimaging and Computer vision.
His research in Computer vision tackles topics such as Mean squared error which are related to areas like Imaging phantom.
His work deals with themes such as Differential diagnosis, Biopsy, Computed tomography and Reproducibility, which intersect with Radiomics.
His work in Deep learning addresses subjects such as Affine transformation, which are connected to disciplines such as Ground truth, 3D ultrasound and Image registration.
He interconnects Robustness, Knee Joint, Radiography and Medical imaging in the investigation of issues within Magnetic resonance imaging.
Between 2018 and 2021, his most popular works were:
- Multimodal Machine Learning-based Knee Osteoarthritis Progression Prediction from Plain Radiographs and Clinical Data. (28 citations)
- Disease progression timeline estimation for Alzheimer's disease using discriminative event based modeling. (24 citations)
- Predicting the 1p/19q Codeletion Status of Presumed Low-Grade Glioma with an Externally Validated Machine Learning Algorithm. (18 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Internal medicine
- Statistics
His primary scientific interests are in Artificial intelligence, Neuroimaging, Machine learning, Pattern recognition and Segmentation.
The study incorporates disciplines such as External validation, Computer vision and Treatment response in addition to Artificial intelligence.
The Pattern recognition study combines topics in areas such as Ground truth and Magnetic resonance imaging.
His studies deal with areas such as Image segmentation and Data curation as well as Magnetic resonance imaging.
Stefan Klein combines subjects such as 3D ultrasound, Deep learning and Atlas with his study of Segmentation.
He performs integrative study on Image registration and Continuous registration.
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