Karl Spuhler
- Radiology, Nuclear Medicine and Imaging top 5%
- Artificial Intelligence top 10%
- Biomedical Engineering
- Orthopedics and Sports Medicine
- Oncology
- Co-authors
- Chuan HuangJie DingYi GaoChunling LiuChanghong LiangShahid HussainChristine DeLorenzoRamin V. Parsey
- Topics
- Radiomics and Machine Learning in Medical Imaging (6 papers)Medical Imaging Techniques and Applications (5 papers)Advanced Neuroimaging Techniques and Applications (4 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingOrthopedics and Sports MedicineArtificial Intelligence
- Partner nations
- United StatesChina
In The Last Decade
Karl Spuhler
14 papers receiving 324 citations
Peers
Comparison fields: 5 of 52
- Radiology, Nuclear Medicine and Imaging 269
- Artificial Intelligence 102
- Biomedical Engineering 56
- Orthopedics and Sports Medicine 31
- Oncology 29
Countries citing papers authored by Karl Spuhler
This map shows the geographic impact of Karl Spuhler's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Karl Spuhler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Karl Spuhler more than expected).
Fields of papers citing papers by Karl Spuhler
This network shows the impact of papers produced by Karl Spuhler. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Karl Spuhler. The network helps show where Karl Spuhler may publish in the future.
Co-authorship network of co-authors of Karl Spuhler
This figure shows the co-authorship network connecting the top 25 collaborators of Karl Spuhler. A scholar is included among the top collaborators of Karl Spuhler based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Karl Spuhler. Karl Spuhler is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 7 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | PET Image Denoising Using Structural MRI with a Novel Dilated Convolutional Neural Network | 7 |
| 6 | 28 | |
| 7 | 151 | |
| 8 | 45 | |
| 9 | 38 | |
| 10 | 29 | |
| 11 | 1 | |
| 12 | 1 | |
| 13 | 11 | |
| 14 | 1 |
About Karl Spuhler
Karl Spuhler is a scholar working on Aging, Radiology, Nuclear Medicine and Imaging and Otorhinolaryngology, having authored 14 papers that have together received 325 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (6 papers), Medical Imaging Techniques and Applications (5 papers) and Advanced Neuroimaging Techniques and Applications (4 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (269 citations), Orthopedics and Sports Medicine (31 citations) and Artificial Intelligence (102 citations). Karl Spuhler has collaborated with scholars based in United States and China. Frequent co-authors include Chuan Huang, Jie Ding, Yi Gao, Chunling Liu, Changhong Liang, Shahid Hussain, Christine DeLorenzo, Ramin V. Parsey, Xintao Zhang and Quan Zhou. Their work appears in journals such as Biological Psychiatry, Biophysical Journal and Magnetic Resonance in Medicine.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.