M. Pesola
- Electrical and Electronic Engineering top 10%
- Radiology, Nuclear Medicine and Imaging top 5%
- Pulmonary and Respiratory Medicine top 10%
- Materials Chemistry
- Atomic and Molecular Physics, and Optics top 10%
- Co-authors
- R. M. NieminenJ. von BoehmS. PöykköM. J. PuskaIvan JamborHarri MerisaariHannu J. AronenPeter J. Boström
- Topics
- Prostate Cancer Diagnosis and Treatment (10 papers)MRI in cancer diagnosis (9 papers)Radiomics and Machine Learning in Medical Imaging (8 papers)
- Cited by
- Radiology, Nuclear Medicine and ImagingHealth InformaticsPulmonary and Respiratory Medicine
- Partner nations
- FinlandUnited StatesNetherlands
In The Last Decade
M. Pesola
32 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 75
- Electrical and Electronic Engineering 424
- Radiology, Nuclear Medicine and Imaging 413
- Pulmonary and Respiratory Medicine 272
- Materials Chemistry 252
- Atomic and Molecular Physics, and Optics 221
Countries citing papers authored by M. Pesola
This map shows the geographic impact of M. Pesola'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 M. Pesola with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Pesola more than expected).
Fields of papers citing papers by M. Pesola
This network shows the impact of papers produced by M. Pesola. 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 M. Pesola. The network helps show where M. Pesola may publish in the future.
Co-authorship network of co-authors of M. Pesola
This figure shows the co-authorship network connecting the top 25 collaborators of M. Pesola. A scholar is included among the top collaborators of M. Pesola 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 M. Pesola. M. Pesola 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 | 1 | |
| 3 | 12 | |
| 4 | 4 | |
| 5 | 79 | |
| 6 | 23 | |
| 7 | 51 | |
| 8 | Diffusion weighted imaging of prostate cancer: Prediction of cancer using texture features from parametric maps of the monoexponential and kurtosis functions | 1 |
| 9 | 6 | |
| 10 | 35 | |
| 11 | 22 | |
| 12 | 21 | |
| 13 | 15 | |
| 14 | 19 | |
| 15 | 54 | |
| 16 | 69 | |
| 17 | 36 | |
| 18 | 13 | |
| 19 | 211 | |
| 20 | [Reading chest radiographs in epidemiologic surveys on pneumoconiosis: a science or art?]. | 1 |
About M. Pesola
M. Pesola is a scholar working on Structural Biology, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine, having authored 32 papers that have together received 1.1k indexed citations. Recurring topics across this work include Prostate Cancer Diagnosis and Treatment (10 papers), MRI in cancer diagnosis (9 papers) and Radiomics and Machine Learning in Medical Imaging (8 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (413 citations), Health Informatics (14 citations) and Pulmonary and Respiratory Medicine (272 citations). M. Pesola has collaborated with scholars based in Finland, United States and Netherlands. Frequent co-authors include R. M. Nieminen, J. von Boehm, S. Pöykkö, M. J. Puska, Ivan Jambor, Harri Merisaari, Hannu J. Aronen, Peter J. Boström, Pekka Taimen and Heikki Minn. Their work appears in journals such as Physical Review Letters, Physical review. B, Condensed matter and Applied Physics Letters.
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.