Julius Keyl

7 papers receiving 154 citations

Julius Keyl's Hit Papers

CellViT: Vision Transformers for precise cell segmentation and classification 2024 · 96 citations
960+1Years since publication255075

Peers

Julius Keyl
Comparison fields: 5 of 36
  • Health Informatics 8
  • Biophysics 25
  • Radiology, Nuclear Medicine and Imaging 63
  • Artificial Intelligence 76
  • Computer Vision and Pattern Recognition 45
Replace Maxime W. Lafarge with:
Maxime W. Lafarge Netherlands
Ruqayya Awan United Kingdom
Dig Vijay Kumar Yarlagadda United States
Niccolò Marini Switzerland
Navid Alemi Koohbanani United Kingdom
Quoc Dang Vu United Kingdom
Zhaoyang Xu China
Minu D. Tizabi Germany
Kutsev Bengisu Ozyoruk United States
Pedro C. Neto Portugal
Julius Keyl relative to Maxime W. Lafarge Netherlands Maxime W. Lafarge's profile →
Citations per field
00.5×3.5×
Maxime W. Lafarge · 1×
Citations per year

Countries citing papers authored by Julius Keyl

Since Specialization
Citations

This map shows the geographic impact of Julius Keyl'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 Julius Keyl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Julius Keyl more than expected).

Fields of papers citing papers by Julius Keyl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Julius Keyl. 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 Julius Keyl. The network helps show where Julius Keyl may publish in the future.

Co-authors

The 25 scholars most cited alongside Julius Keyl, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Julius Keyl Line = papers co-authored together Julius Keyl links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1
CellViT: Vision Transformers for precise cell segmentation and classification
Hit paper breakdown →
202496
2 202227
3 202219
4 20236
5 20225
6 20231
7 20251
8 20250

About Julius Keyl

Julius Keyl is a scholar working on Radiology, Nuclear Medicine and Imaging, Oncology, Artificial Intelligence, Pulmonary and Respiratory Medicine and Computer Vision and Pattern Recognition, having authored 8 papers that have together received 155 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (6 papers), AI in cancer detection (3 papers), Colorectal Cancer Screening and Detection (2 papers), Digital Imaging for Blood Diseases (1 paper), Lung Cancer Diagnosis and Treatment (1 paper), Computational Drug Discovery Methods (1 paper), Pancreatic and Hepatic Oncology Research (1 paper) and Artificial Intelligence in Healthcare and Education (1 paper). The work is most often cited by research in Health Informatics (8 citations), Biophysics (25 citations), Radiology, Nuclear Medicine and Imaging (63 citations), Artificial Intelligence (76 citations) and Computer Vision and Pattern Recognition (45 citations). Julius Keyl has collaborated with scholars based in Germany, Canada and Chile. Frequent co-authors include Jens Kleesiek, Jens T. Siveke, Jan Egger, Barbara T. Grünwald, Constantin Seibold, Selma Ugurel, Giulia Baldini, Martin Schüler, Brigitte Schumacher and Jürgen Treckmann. Their work appears in journals such as Journal of Cachexia Sarcopenia and Muscle, ESMO Open, Medical Image Analysis, Computerized Medical Imaging and Graphics and Annals of Oncology.

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.

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