M. Pesola

1.3k total citations
32 papers, 1.1k citations indexed

About

M. Pesola is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Electrical and Electronic Engineering. According to data from OpenAlex, M. Pesola has authored 32 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Radiology, Nuclear Medicine and Imaging, 12 papers in Pulmonary and Respiratory Medicine and 9 papers in Electrical and Electronic Engineering. Recurrent topics in M. Pesola's 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). M. Pesola is often cited by papers focused on Prostate Cancer Diagnosis and Treatment (10 papers), MRI in cancer diagnosis (9 papers) and Radiomics and Machine Learning in Medical Imaging (8 papers). M. Pesola collaborates with scholars based in Finland, United States and Netherlands. M. Pesola's 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 and has published in prestigious journals such as Physical Review Letters, Physical review. B, Condensed matter and Applied Physics Letters.

In The Last Decade

M. Pesola

32 papers receiving 1.1k citations

Peers

M. Pesola
H. Otsu Japan
Peter G. Hawkins United States
Ryan Brown United States
M. Pesola
Citations per year, relative to M. Pesola M. Pesola (= 1×) peers Kenkichi Tanioka

Countries citing papers authored by M. Pesola

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

20 of 20 papers shown
1.
Jambor, Ivan, M. Pesola, Maria Gardberg, et al.. (2024). Relaxation Along a Fictitious Field, continuous wave T1rho, adiabatic T1rho and adiabatic T2rho imaging of human gliomas at 3T: A feasibility study. PLoS ONE. 19(4). e0296958–e0296958. 2 indexed citations
2.
Jambor, Ivan, M. Pesola, Timo Liimatainen, et al.. (2021). Whole Brain Adiabatic T1rho and Relaxation Along a Fictitious Field Imaging in Healthy Volunteers and Patients With Multiple Sclerosis: Initial Findings. Journal of Magnetic Resonance Imaging. 54(3). 866–879. 1 indexed citations
3.
Kuisma, Anna, Jani Keyriläinen, Sami Suilamo, et al.. (2020). Validation of automated magnetic resonance image segmentation for radiation therapy planning in prostate cancer. Physics and Imaging in Radiation Oncology. 13. 14–20. 12 indexed citations
4.
Movahedi, Parisa, Harri Merisaari, Ileana Montoya Perez, et al.. (2020). Prediction of prostate cancer aggressiveness using 18F-Fluciclovine (FACBC) PET and multisequence multiparametric MRI. Scientific Reports. 10(1). 4 indexed citations
5.
Perez, Ileana Montoya, Parisa Movahedi, Harri Merisaari, et al.. (2019). Radiomics and machine learning of multisequence multiparametric prostate MRI: Towards improved non-invasive prostate cancer characterization. PLoS ONE. 14(7). e0217702–e0217702. 79 indexed citations
6.
Suilamo, Sami, et al.. (2019). Assessment of dosimetric and positioning accuracy of a magnetic resonance imaging-only solution for external beam radiotherapy of pelvic anatomy. Physics and Imaging in Radiation Oncology. 11. 1–8. 23 indexed citations
7.
Pesola, M., Teemu Saari, Juho Raiko, et al.. (2017). MR signal-fat-fraction analysis and T2* weighted imaging measure BAT reliably on humans without cold exposure. Metabolism. 70. 23–30. 51 indexed citations
8.
Movahedi, Parisa, et al.. (2016). Diffusion weighted imaging of prostate cancer: Prediction of cancer using texture features from parametric maps of the monoexponential and kurtosis functions. IEEE Conference Proceedings. 2016. 6. 1 indexed citations
9.
Perez, Ileana Montoya, Parisa Movahedi, Harri Merisaari, et al.. (2016). Diffusion weighted imaging of prostate cancer: Prediction of cancer using texture features from parametric maps of the monoexponential and kurtosis functions. 33. 1–6. 6 indexed citations
10.
Kiviniemi, Aida, Maria Gardberg, Janek Frantzén, et al.. (2015). Serum levels of GFAP and EGFR in primary and recurrent high-grade gliomas: correlation to tumor volume, molecular markers, and progression-free survival. Journal of Neuro-Oncology. 124(2). 237–245. 35 indexed citations
11.
Merisaari, Harri, M. Pesola, Pekka Taimen, et al.. (2015). Diffusion-weighted imaging of prostate cancer: effect of b-value distribution on repeatability and cancer characterization. Magnetic Resonance Imaging. 33(10). 1212–1218. 22 indexed citations
12.
Kiviniemi, Aida, Maria Gardberg, Janek Frantzén, et al.. (2015). Somatostatin receptor subtype 2 in high-grade gliomas: PET/CT with 68Ga-DOTA-peptides, correlation to prognostic markers, and implications for targeted radiotherapy. EJNMMI Research. 5(1). 25–25. 21 indexed citations
13.
Jambor, Ivan, M. Pesola, Harri Merisaari, et al.. (2015). Relaxation along fictitious field, diffusion-weighted imaging, and T2mapping of prostate cancer: Prediction of cancer aggressiveness. Magnetic Resonance in Medicine. 75(5). 2130–2140. 15 indexed citations
14.
Jambor, Ivan, M. Pesola, Pekka Taimen, et al.. (2015). Rotating frame relaxation imaging of prostate cancer: Repeatability, cancer detection, and Gleason score prediction. Magnetic Resonance in Medicine. 75(1). 337–344. 19 indexed citations
15.
Merisaari, Harri, M. Pesola, Pekka Taimen, et al.. (2014). Mathematical models for diffusion‐weighted imaging of prostate cancer using b values up to 2000 s/mm2: Correlation with Gleason score and repeatability of region of interest analysis. Magnetic Resonance in Medicine. 74(4). 1116–1124. 54 indexed citations
16.
Jambor, Ivan, Harri Merisaari, Pekka Taimen, et al.. (2014). Evaluation of different mathematical models for diffusion-weighted imaging of normal prostate and prostate cancer using high b-values: A repeatability study. Magnetic Resonance in Medicine. 73(5). 1988–1998. 69 indexed citations
17.
Lee, Young Joo, J. von Boehm, M. Pesola, & R. M. Nieminen. (2001). Aggregation Kinetics of Thermal Double Donors in Silicon. Physical Review Letters. 86(14). 3060–3063. 36 indexed citations
18.
Pesola, M., et al.. (2000). Vacancies in SiGe: Jahn–Teller distortion and spin effects. Applied Physics Letters. 77(2). 232–234. 13 indexed citations
19.
Puska, M. J., S. Pöykkö, M. Pesola, & R. M. Nieminen. (1998). Convergence of supercell calculations for point defects in semiconductors: Vacancy in silicon. Physical review. B, Condensed matter. 58(3). 1318–1325. 211 indexed citations
20.
Assennato, Giorgio, et al.. (1983). [Reading chest radiographs in epidemiologic surveys on pneumoconiosis: a science or art?].. PubMed. 74(1). 51–6. 1 indexed citations

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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