Publications

My MR Author ID in MathSciNet is 832714,
researcherID in Web of Sciences is G-4339-2016,
Orcid ID in Scopus is 0000-0002-0982-8360 and
here is my Google Scholar profile.

List of publications

* shared first author

** member of consortium

 

  1. A. Li, M.K. Jaakkola, T. Saaresranta, R. Klén, X.-G. Li: Analysis of sleep apnea research with a special focus on the use of positron emission tomography as a study tool. Sleep Med. Rev. 77 (2024). https://doi.org/10.1016/j.smrv.2024.101967
  2. O. Rainio, J. Tamminen, M.S. Venäläinen, J. Liedes, J. Knuuti, J. Kemppainen, R. Klén: Comparison of thresholds for a convolutional neural network classifying medical images. Int. J. Data Sci. Anal. (2024). https://doi.org/10.1007/s41060-024-00584-z
  3. T. Rudroff, O. Rainio, R. Klén: AI for the Prediction of Early Stages of Alzheimer’s Disease from Neuroimaging Biomarkers – A narrative review of a growing field. Neurol. Sci. (2024). https://doi.org/10.1007/s10072-024-07649-8, https://arxiv.org/abs/2406.17822
  4. J. Teuho, J. Schultz, R. Klén, L.E. Juarez-Orozco, J. Knuuti, A. Saraste, N. Ono, S. Kanaya: Explainable deep learning-based ischemia detection using hybrid O-15 H2O perfusion PET/CT imaging and clinical data. J. Nucl. Cardiol. (2024). https://doi.org/10.1016/j.nuclcard.2024.101889
  5. M. Jafaritadi, J. Teuho, E. Lehtonen, R. Klén, A. Saraste, C.S. Levin: Deep generative denoising networks enhance quality and accuracy of gated cardiac PET data. Ann. Nucl. Med. (2024). https://doi.org/10.1007/s12149-024-01945-1
  6. O. Rainio, J. Teuho, R. Klén: Evaluation metrics and statistical tests for machine learning. Sci. Rep. 14 (2024), Article number: 6086. https://doi.org/10.1038/s41598-024-56706-x
  7. O. Rainio, R. Klén: Comparison of Simple Augmentation Transformations for a Convolutional Neural Network Classifying Medical Images. Signal Image Video P. (2024). https://doi.org/10.1007/s11760-024-02998-5
  8. E. Lehtonen*, I. Kujala*, J. Tamminen, T. Maaniitty, A. Saraste, J. Teuho, J. Knuuti, R. Klén: Incremental prognostic value of downstream positron emission tomography perfusion imaging after coronary computed tomography angiography: a study using machine learning. Eur. Heart J. Cardiovasc. Imaging 25 (2024). https://doi.org/10.1093/ehjci/jead246
  9. S.M. Hosseini, R.M. Moghaddam, J. Schultz, A. Saraste, R. Klén, J. Teuho: Explainable AI and Transfer Learning in the Classification of PET Cardiac Perfusion Polar Maps. IEEE Nuclear Science Symposium, Medical Imaging Conference and International Symposium on Room-Temperature Semiconductor Detectors (NSS MIC RTSD), 2023. doi: https://doi.org/10.1109/NSSMICRTSD49126.2023.10338595
  10. M.K. Jaakkola, M. Rantala, A. Jalo, T. Saari, J. Hentilä, J.S. Helin, T.A. Nissinen, O. Eskola, J. Rajander, K.A. Virtanen, J.C. Hannukainen, F. López-Picón, R. Klén: Segmentation of dynamic total-body [18F]-FDG PET images using unsupervised clustering. Int. J. Biomed. Imaging, vol. 2023 (2023), Article ID 3819587, 13 pages. https://doi.org/10.1155/2023/3819587
  11. O. Rainio, M. Nasser, M. Vuorinen, R. Klén: Image augmentation with conformal mappings for a convolutional neural network. Comput. Appl. Math. Preprint 42, Article number: 361 (2023). https://doi.org/10.1007/s40314-023-02501-9
  12. J. Knuuti, J. Tuisku, H. Kärpijoki, H. Iida, T. Maaniitty, A. Latva-Rasku, V. Oikonen, S. Nesterov, J. Teuho, M.K. Jaakkola, R Klén, H. Louhi, V. Saunavaara, P. Nuutila, A. Saraste, J. Rinne, L. Nummenmaa: Quantitative perfusion imaging with total body positron emission tomography. J. Nucl. Med. 2023 Nov;64(Suppl 2):11S-19S. https://doi.org/10.2967/jnumed.122.264870
  13. O. Rainio, J. Lahti, M. Anttinen, O. Ettala, M. Seppänen, P. Boström, J. Kemppainen, R. Klén: New method of using a convolutional neural network for 2D intraprostatic tumor segmentation from PET images. Res. Biomed. Eng. (2023). https://doi.org/10.1007/s42600-023-00314-7
  14. R. Klén*, I.A. Huespe*, F. Gregalio, A.L. Blanco, P.R. Valdez, M.A. Mirofsky, B. Boietti, R. Gómez-Huelgas, J.M. Casas-Rojo, J.M. Antón-Santos, J.A. Pollán, D. Gómez-Varela: Development and validation of COEWS (COVID-19 Early Warning Score) for hospitalized COVID-19 with laboratory features: A multicontinental retrospective study. eLife 2023, 12:e85618.
    https://doi.org/10.7554/eLife.85618
  15. T. Maaniitty, R. Jukema, P. Van Diemen, W. Nammas, I. Stenstrom, M. Maenpaa, I. Kujala, P.G. Raijmakers, R. Sprengers, R.N. Planken, R. Klen, P. Knaapen, A. Saraste, J. Knuuti, I. Danad: The time-dependent prognostic value of coronary computed tomography angiography in symptomatic patients. Eur. Heart J. Cardiovasc. Imaging 24 (2023). https://doi.org/10.1093/ehjci/jead119.263
  16. J. Liedes, H. Hellström, O. Rainio, S. Murtojärvi, S. Malaspina, J. Hirvonen, R. Klén, J. Kemppainen: Automatic segmentation of head and neck cancer from PET-MRI data using deep learning. J. Med. Biol. Eng. (2023). https://doi.org/10.1007/s40846-023-00818-8
  17. L.E. Juarez-Orozco, M. Niemi, M.W. Yeung, J.W. Benjamins, T. Maaniitty, J. Teuho, A. Saraste, J. Knuuti, P. van der Harst, R. Klén: Hybridizing machine learning in survival analysis of cardiac PET/CT imaging. J. Nucl. Cardiol. (2023). https://doi.org/10.1007/s12350-023-03359-4
  18. H. Hellström, J. Liedes, O. Rainio, S. Malaspina, J. Kemppainen, R. Klén: Classification of head and neck cancer from PET images using convolutional neural networks. Sci. Rep. 13 (2023), Article number: 10528. https://doi.org/10.1038/s41598-023-37603-1
  19. P. Harjulehto, R. Klén, M. Koskenoja: Analyysiä reaaliluvuilla, 6th edition, Unigrafia, Helsinki, 2023, 370 pages, ISBN 978-952-34-5249-7; 978-952-34-5423-1. (A calculus textbook for the first year students.)
  20. I.A. Huespe, A. Ferraris, A.L. Blanco, P.R. Valdez, L. Peroni, L.A. Cayetti, M.A. Mirofsky, B. Boietti, R. Gómez-Huelgas, J.M. Casas-Rojo, J.M. Antón-Santos, J.M. Núñez-Cortés, C. Lumbreras, J.M. Ramos-Rincón, N.G. Barrio, M. Pedrera-Jiménez, M.D. Martin-Escalante, F. Rivas Ruiz, M.A. Onieva-García, C.R. Toso, M.R. Risk, R. Klén, J.A. Pollán, D. Gómez-Varela: COVID-19 vaccines reduce mortality in hospitalized patients with oxygen requirements: Differences between vaccine subtypes. Multicontinental cohort Study. J. Med. Virol. 95:5 (2023), e28786. https://doi.org/10.1002/jmv.28786
  21. H. Keemu, K.J. Alakylä, R. Klén, V.J. Panula, M.S. Venäläinen, J.J. Haapakoski, A.P. Eskelinen, K. Pamilo, J.S. Kettunen, A.-P. Puhto, A.I. Vasara, L.L. Elo, K.T. Mäkelä: Risk factors for prosthetic joint infection revision following total knee arthroplasty based on 62,087 knees in the Finnish Arthroplasty Register from 2014 to 2020. Acta Orthop. 94 (2023), 215–223. https://doi.org/10.2340/17453674.2023.12307
  22. O. Rainio, C. Han, J. Teuho, S.V. Nesterov, V. Oikonen, S. Piirola, T. Laitinen, M. Tättäläinen, J. Knuuti, R. Klén: Carimas: An extensive medical imaging data processing tool for research. J. Digit. Imaging (2023). doi: https://doi.org/10.1007/s10278-023-00812-1
  23. I. Kujala, W. Nammas, T. Maaniitty, I. Stenström, R. Klén, J. J Bax, J. Knuuti, Antti Saraste: Prognostic value of combined coronary CT angiography and myocardial perfusion imaging in women and men. Eur. Heart J. Cardiovasc. Imaging (2023), jead072. doi: https://doi.org/10.1093/ehjci/jead072
  24. I. Huespe, J. Pollan, A. Khalid, A. Ferraris, A. Blanco, R. Gómez-Huelgas, A. Miguel, J. Nuñes-Cortes, C. Lumbreras, J. Rincon, N. Barrio, J. Casas-Rojo, P. Valdez, M. Mirofsky, B. Boietti, R. Klén, L. Cayetti, F. Ruiz, J. Sinner, D. Varela: 907: COVID-19 Vaccine Protection Against Mortality In Patients With Oxygen: A Multicontinental Study. Crit. Care Med. 51 (2023), 446-446. doi: https://doi.org/10.1097/01.ccm.0000909356.97905.63
  25. R. Klén, D. Purohit, R. Gómez-Huelgas, J.M. Casas-Rojo, J.M.A. Santos, J.M. Núñez-Cortés, C. Lumbreras, J.M. Ramos-Rincón, P. Young, J.I. Ramírez, E.E.T. Omonte, R.G. Artega, M.T.C. Beltrán, P. Valdez, F. Pugliese, R. Castagna, N. Funke, B. Leiding, D. Gómez-Varela: Development and evaluation of a machine learning-based in-hospital COvid-19 Disease Outcome Predictor (CODOP): a multicontinental retrospective study. eLife 2022, 11:e75985. doi: https://doi.org/10.7554/eLife.75985
  26. J. Lindén*, J. Teuho*, R. Klén, M. Teräs: Are quantitative errors reduced with time-of-flight reconstruction when using imperfect MR-based attenuation maps for 18F-FDG PET/MR neuroimaging?. Appl. Sci. 2022, 12(9), 4605. doi: https://doi.org/10.3390/app12094605
  27. A. Subasi, S.S. Panigrahi, B.S. Patil, M.A. Canbaz, R. Klén: Chapter 8 – Advanced pattern recognition tools for disease diagnosis. Chapter in book In 5G IoT and Edge Computing for Smart Healthcare, Intelligent Data-Centric Systems, Academic Press, 2022, Pages 195-229, ISBN 9780323905480. https://doi.org/10.1016/B978-0-323-90548-0.00011-5
  28. J. Lindén*, J. Teuho*, M. Teräs, R. Klén: Evaluation of three methods for delineation and attenuation estimation of the sinus region in MR-based attenuation correction for brain PET-MR imaging. BMC Medical Imaging volume 22, Article number: 48 (2022). https://doi.org/10.1186/s12880-022-00770-0
  29. J. Teuho, J. Schultz, R. Klén, J. Knuuti, A. Saraste, N. Ono, S. Kanaya: Novel Classification of ischemia from myocardial polar maps in 15O–H2O cardiac perfusion imaging using a convolutional neural network. Sci. Rep. 12 (2022), Article number: 2839. doi: https://doi.org/10.1038/s41598-022-06604-x
  30. L.E. Juarez-Orozco, R. Klén, M. Niemi, B. Ruijsink, G. Daquarti, R. van Es, J.-W. Benjamins, M. Yeung, P. van der Harst, J. Knuuti: Artificial Intelligence to Improve Risk Prediction with Nuclear Cardiac Studies. Curr. Cardiol. Rep. (2022). doi: https://doi.org/10.1007/s11886-022-01649-w
  31. S. Laurila, E. Rebelos, M. Lahesmaa, L. Sun, K. Schnabl, T.-M. Peltomaa, R. Klén, M. U-Din, M.-J. Honka, O. Eskola, A.K. Kirjavainen, L. Nummenmaa, M. Klingenspor, K.A. Virtanen, P. Nuutila: Novel Effects of the Gastrointestinal Hormone Secretin on Cardiac Metabolism and Renal Function. Am. J. Physiol. Endocrinol. Metab. 322:1 (2022), E54-E62. doi: https://doi.org/10.1152/ajpendo.00260.2021
  32. J. Schultz, R. Siekkinen, M.J. Tadi, M. Teräs, R. Klén, E. Lehtonen, A. Saraste, J. Teuho: Effect of respiratory motion correction and CT-based attenuation correction on dual-gated cardiac PET image quality and quantification. J. Nucl. Cardiol. 29, pages 2423–2433 (2022). doi: https://doi.org/10.1007/s12350-021-02769-6
  33. J. Teuho, J. Schultz, R. Klén, A. Saraste, N. Ono, S. Kanaya: Comparison of 12 Machine Learning Methods for Polar Map Classification in Cardiac Perfusion PET. IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2021. doi: https://doi.org/10.1109/NSS/MIC44867.2021.9875597
  34. M. Venäläinen, V. Panula, R. Klén, J. Haapakoski, A. Eskelinen, M. Manninen, J. Kettunen, A.-P. Puhto, A. Vasara, K. Mäkelä, L. Elo: Riskilaskurimallit tyypillisimmille lyhyen aikavälin komplikaatioille sekä kuolemalle ensivaiheen lonkan kokotekonivelleikkauksen jälkeen perustuen Suomen Endoproteesirekisterin tietokantaan. Suomen ortopedia ja traumatologia (2021).
  35. J. Rives Gambin, M.J. Tadi, J. Teuho, R. Klén, J. Knuuti, J. Koskinen, A. Saraste, E. Lehtonen: Learning to Denoise Gated Cardiac PET Images Using Convolutional Neural Networks. IEEE Access (2021). doi: https://doi.org/10.1109/ACCESS.2021.3122194
  36. V.J. Panula, E.M. Ekman, M.S. Venäläinen, I. Laaksonen, R. Klén, J.J. Haapakoski, A.P. Eskelinen, L.L. Elo, K.T. Mäkelä: Posterior approach, fracture diagnosis and ASA class III-IV are associated with increased risk of revision for dislocation after total hip arthroplasty: An analysis of 33,337 operations from the Finnish Arthroplasty Register. Scand. J. Surg. 110
    (2021), 351-358. doi: https://doi.org/10.1177/1457496920930617
  37. M. Mahmoudian*, M.S. Venäläinen*, R. Klén*, L.L. Elo: Stable Iterative Variable Selection. Bioinformatics 2021, btab501. doi: https://doi.org/10.1093/bioinformatics/btab501
  38. S. Laurila, L. Sun, M. Lahesmaa, K. Schnabl, K. Laitinen, R. Klén, Y. Li, M. Balaz, C. Wolfrum, K. Steiger, T. Niemi, M. Taittonen, M. U-Din, T. Välikangas, L.L. Elo, O. Eskola, A.K. Kirjavainen, L. Nummenmaa, K.A. Virtanen, M. Klingenspor, P. Nuutila: Secretin Activates Brown Fat and Induces Satiation. Nat. Metab. 3 (2021), 798-809.
  39. E. Lehtonen, J. Teuho, J. Koskinen, M.J. Tadi, R. Klén, R. Siekkinen, J. Rives Gambin, T. Vasankari, A. Saraste: A Respiratory Motion Estimation Method Based on Inertial Measurement Units for Gated Positron Emission Tomography. Sensors 2021, 21, 3983.
  40. J.W. Benjamins, M.W. Yeung, T. Maaniitty, A. Saraste, R. Klén, P. van der Harst, J. Knuuti, L. Eduardo Juarez-Orozco: Improving patient identification for advanced cardiac imaging through machine learning-integration of clinical and coronary CT angiography data. Int. J. Cardiol. 335 (2021), 130-136.
  41. S. Sieberts, J. Schaff, M. Duda, B. Pataki, M. Sun, P. Snyder, J.-F. Daneault, F. Parisi, G. Costante, U. Rubin, P. Banda, Y. Chae, E. Neto, E. Dorsey, Z. Aydin, A. Chen, L. Elo, C. Espino, E. Glaab, E. Goan, F. Golabchi, Y. Görmez, M. Jaakkola, J. Jonnagaddala, R. Klén, D. Li, C. McDaniel, D. Perrin, N. Rad, T. Perumal, E. Rainaldi, S. Sapienza, P. Schwab, N. Shokhirev, M. Venäläinen, G. Vergara-Diaz, Y. Zhang, Y. Wang, The Parkinson’s Disease Digital Biomarker Challenge Consortium, Y. Guan, D. Brunner, P. Bonato, L. Mangravite, L. Omberg: Crowdsourcing digital health measures to predict Parkinson’s disease severity: the Parkinson’s Disease Digital Biomarker DREAM Challenge. NPJ Digit. Med. 4, Article number: 53 (2021).
  42. M. Venäläinen, S. Mikko, V. Panula, R. Klén, J. Haapakoski, A.P. Eskelinen, M.J. Manninen, J. Kettunen, A.-P. Puhto, A. Vasara, K. Mäkelä, L.L. Elo: Preoperative Risk Prediction Models for Short-Term Revision and Death After Total Hip Arthroplasty. JBJS Open Access: January-March 2021 – Volume 6 – Issue 1 – p e20.00091 doi: 10.2106/JBJS.OA.20.00091
  43. E. Harmaala, R. Klén: Ptolemy constant and uniformity. Publ. Math. Debrecen 98/1-2 (2021), 15-42. (arXiv)
  44. R. Siekkinen, E. Lehtonen, J. Teuho, M. J. Tadi, J. Koskinen, R. Klén: Validation of Automated PET Segmentation Methods Based on Connected Components for Myocardium. IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 2020, pp. 1-7. doi: https://doi.org/10.1109/NSS/MIC42677.2020.9508011
  45. J. Teuho, L. Riehakainen, A. Honkaniemi, O. Moisio, C. Han, M. Tirri, S. Liu, T.J. Grönroos, J. Liu, L. Wan, X. Liang, Y. Ling, Y. Hua, A. Roivainen, J. Knuuti, Q. Xie, M. Teräs, N. D’Ascenzo, R. Klén: Evaluation of Image Quality with Four Positron Emitters and Three Preclinical PET/CT Systems. EJNMMI Research volume 10, Article number: 155 (2020).
  46. R. Klén*, J. Teuho*, T. Noponen, K. Thielemnas, E. Hoppela, E. Lehtonen, H.T. Sipila, M. Teräs, J. Knuuti: Estimation of Optimal Number of Gates in Dual Gated 18F-FDG Cardiac PET. Sci. Rep. 10 (2020), Article number: 19362.
  47. I. Ranta, J. Teuho, J. Linden, R. Klén, M. Teräs, M. Kapanen, J. Keyriläinen: Assessment of MRI-Based Attenuation Correction for MRI-Only Radiotherapy Treatment Planning of the Brain. Diagnostics 10 (2020), 299.
  48. P. Hariri, R. Klén, M. Vuorinen: Conformally Invariant Metrics and Quasiconformal Mappings, Springer Monographs in Mathematics. Springer, 2020. xix+502 pages, ISBN 978-3-030-32068-3; 978-3-030-32067-6.
  49. R. Klén*, M.-J. Honka*, J.C. Hannukainen, V. Huovinen, M. Bucci, A. Latva-Rasku, M.S. Venäläinen, K.K. Kalliokoski, K.A. Virtanen, R. Lautamäki, P. Iozzo, L.L. Elo, P. Nuutila: Predicting skeletal muscle and whole-body insulin sensitivity using NMR-metabolomic profiling. J. Endocr. Soc. (2020), bvaa026.
  50. M.S. Venäläinen, R. Klén, M. Mahmoudian, O.T. Raitakari, L.L. Elo: Easy-to-use tool for evaluating the elevated acute kidney injury risk against reduced cardiovascular disease risk during intensive blood pressure control. J. Hypertens. 38 (2020), 511-518.
  51. M.J. Mason, C. Schinke, C.L.P. Eng, F. Towfic, F. Gruber, A. Dervan, B.S. White, A. Pratapa, Y. Guan, H. Chen, Y. Cui, B. Li, T. Yu, E. Chaibub Neto, K. Mavrommatis, M. Ortiz, V. Lyzogubov, K. Bisht, H.Y. Dai, F. Schmitz, E. Flynt, D. Rozelle, S.A. Danziger, A. Ratushny, Multiple Myeloma DREAM Consortium**, W.S. Dalton, H. Goldschmidt, H. Avet-Loiseau, M. Samur, B. Hayete, P. Sonneveld, K.H. Shain, N. Munshi, D. Auclair, D. Hose, G. Morgan, M. Trotter, D. Bassett, J. Goke, B.A. Walker, A. Thakurta, J. Guinney: Multiple Myeloma DREAM Challenge reveals epigenetic regulator PHF19 as marker of aggressive disease.
    Leukemia (2020).
  52. R. Klén*, M. Karhunen*, L.L. Elo: Likelihood contrasts: a machine learning algorithm for binary classification of longitudinal data. Sci. Rep. 10 (2020), Article number: 1016.
  53. J. Teuho, A. Torrado-Carvaja, H. Herzog, U. Anazodo, R. Klén, H. Iida, M. Teräs: Magnetic Resonance-Based Attenuation Correction and Scatter Correction in Neurological Positron Emission Tomography/Magnetic Resonance Imaging-Current Status With Emerging Applications.. Front. Phys. 7 (2020).
  54. A.P. Salminen, I. Montoya Perez, R. Klén, O.O. Ettala, K.T. Syvänen, L.L. Elo, P.J. Boström: Adverse Events During Neoadjuvant Chemotherapy for Muscle Invasive Bladder Cancer. Bladder Cancer 5 (2019), 273-279.
  55. R. Klén*, A. Salminen*, M. Mahmoudian, K.T. Syvänen, L.L. Elo, P.J. Boström: Prediction of complication related death after radical cystectomy for bladder cancer with machine learning methodology. Scand. J. Urol. 53 (2019), 325-331.
  56. M.J. Tadi, E. Lehtonen, J. Teuho, J. Koskinen, J. Schultz, R. Siekkinen, T. Koivisto, M. Pänkäälä, M. Teräs, R. Klén: A Computational Framework for Data Fusion in MEMS-Based Cardiac and Respiratory Gating. Sensors 19 (2019), 4137.
  57. D. Chakroborty*, M.R. Emani*, R. Klén*, C. Böckelman, J. Hagström, C. Haglund, A. Ristimäki, R. Lahesmaa, L.L. Elo: L1TD1 – a prognostic marker for colon cancer. BMC Cancer 19 (2019), Article number: 727.
  58. S. Fourati*, A. Talla*, M. Mahmoudian*, J.G. Burkhart*, R. Klén*, R. Henao, Z. Aydin, K.Y. Yeung, M. Eren Ahsen, R. Almugbel, S. Jahandideh, X. Liang, T.E.M. Nordling, M. Shiga, A. Stanescu, R. Vogel, The Respiratory Viral DREAM Challenge Consortium, G. Pandey, C. Chiu, M.T. McClain, C.W. Woods, G.S. Ginsburg, L.L. Elo, E.L. Tsalik, L.M. Mangravite, S.K. Sieberts: A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection. Nat. Com. 9, Article number: 4418 (2018). (bioRxiv)
  59. V. Panula, E. Ekman, M. Venäläinen, I. Laaksonen, R. Klén, J. Haapakoski, A. Eskelinen, L. Elo, K. Mäkelä: Tekonivelen sijoiltaanmenoon myötävaikuttavat tekijät lonkan tekonivelleikkauksen jälkeen. Suomen ortopedia ja traumatologia 41:2 (2018), 137-141.
  60. M.K. Jaakkola, A.J. McGlinchey, R. Klén, L.L. Elo: PASI: a novel pathway method to identify delicate group effects. PLoS ONE 13(7): e0199991.
  61. P. Hariri, R. Klén, M. Vuorinen: Local convexity of metric balls. Monatsh. Math. 186 (2018), 281-298. (arXiv)
  62. R. Klén: Hyperbolic distance between hyperbolic lines. Ann. Math. Inform. 47 (2017), 129-139.
  63. R. Klén, G. Martin: Distortion and topology. J. Anal. Math. 133 (2017), 229-251. (arXiv)
  64. X. Zhang, R. Klén, V. Suomala, M. Vuorinen: Volume growth of quasihyperbolic balls. Mat. Sb. 208 (2017), no. 6, 902-914. (arXiv)
  65. R. Klén, V. Todorcevic, M. Vuorinen: Teichmüller’s problem in space. J. Math. Anal. Appl. 455 (2017), 1297-1316. (arXiv)
  66. B.A. Bhayo, R. Klén, J. Sándor: New trigonometric and hyperbolic inequalities. Miskolc Math. Notes 18 (2017), no. 1, 125-137. (arXiv)
  67. P. Hariri, R. Klén, M. Vuorinen, X. Zhang: Some remarks on the Cassinian metric. Publ. Math. Debrecen 90/3-4 (2017), 269-285. (arXiv)
  68. R. Klén: Hyperbolic type distances in starlike domains. Results Math. 72 (2017), 47-69. (arXiv)
  69. R. Klén, J. Talponen, A. Rasila: On Smoothness of Quasihyperbolic Balls. Ann. Acad. Sci. Fenn. Math. 42 (2017), 439-452. (arXiv)
  70. R. Klén, M.R. Mohanpatra, S.K. Sahoo: Geometric properties of the Cassinian metric. Math. Nachr. 290 (2017), no. 10, 1, 1531-1543. (arXiv)
  71. P. Hästö, R. Klén, S. Sahoo, M. Vuorinen: Geometric properties of phi-uniform domains. J. Analysis 24 (2016), 57-66. (arXiv)
  72. P. Harjulehto, P. Hästö, R. Klén: Generalized Orlicz spaces and related PDE, Nonlinear Anal. 143 (2016), Pages 155-173.
  73. R. Klén, T. Noponen, J. Koikkalainen, J. Lötjönen, K. Thielemans, E. Hoppela, H. Sipilä, M. Teräs, J. Knuuti: Evaluation of motion-correction methods for dual-gated cardiac positron emission tomography/computed tomography imaging, Nucl. Med. Commun. 37(9), 2016, 956-68.
  74. R. Klén, M. Vuorinen, X. Zhang: On isometries of Conformally Invariant Metric, J. Geom. Anal. 26 (2016), 914-923. (arXiv)
  75. S. Hokuni, R. Klén Y. Li, M. Vuorinen: Balls in the triangular ratio metric, Complex Analysis and Dynamical Systems VI. Part 2, 105-123, Contemp. Math. 667, Amer. Math.
    Soc., Providence, RI, 2016. (arXiv)
  76. P. Hästö, R. Klén: Solution of two conjectures of Klén, Lindén, Vuorinen and Wang. Comput. Methods Funct. Theory 16 (2016), 283-286.
  77. T. Kokki, R. Klén, T. Noponen, J. Pärkkä, V. Saunavaara, E. Hoppela, M. Teräs, J. Knuuti: Linear relation between spirometric volume and the motion of cardiac structures – MRI and clinical PET study. J. Nucl. Cardiol. 23 (2016), 475-485.
  78. T. Noponen, R. Klén, T. Kokki, J. Teuho, K. Thielemans, J. Koikkalainen, E. Hoppela, H. Sipilä, J. Lötjönen, M. Teräs, J. Knuuti: Development of Motion Correction Methods for Cardiac PET Imaging. Eur. J. Nucl. Med. Mol. Imaging 42 (2015), S72-S72.
  79. P. Harjulehto, R. Klén: Examples of fractals satisfying the quasihyperbolic boundary condition. Aust. J. Math. Anal. Appl. 12 (2015), no. 1, Art. 9. (arXiv)
  80. J. Chen, P. Hariri, R. Klén, M. Vuorinen: Lipschitz conditions, triangular ratio metric, and quasiconformal maps. Ann. Acad. Sci. Fenn. Math. 40, 2015, 683-709. (arXiv)
  81. A. Baricz, B.A. Bhayo, R. Klén: Convexity properties of generalized trigonometric and hyperbolic functions. Aequationes Math. Volume 89, Issue 3 (2015), 473-484. (arXiv)
  82. R. Klén, H. Lindén, M. Vuorinen, G. Wang: The visual angle metric and Möbius transformations – Comput. Methods Funct. Theory 14 (2014), Issue 2-3, pp 577-608. (arXiv)
  83. R. Klén, Y. Li, S.K. Sahoo, M. Vuorinen: On the stability of phi-uniform domains. Monatsh. Math. 174 (2014), Issue 2, pp 231–258. (arXiv)
  84. R. Klén, V. Manojlovic, S. Simic, M. Vuorinen: Bernoulli inequality and hypergeometric functions. Proc. Amer. Math. Soc. 142 (2014), 559-573 , (arXiv)
  85. R. Klén, M. Vuorinen, X. Zhang: Quasihyperbolic metric and Möbius transformations. Proc. Amer. Math. Soc. 142 (2014), no. 1, 311-322, (arXiv)
  86. R. Klén, M. Vuorinen, X. Zhang: Inequalities for the generalized trigonometric and hyperbolic functions. J. Math. Anal. Appl 409 (2014), no. 1, 521-529. (arXiv)
  87. R. Klén: Local convexity properties of Apollonian and Seittenranta’s metric balls. Conform. Geom. Dyn. 17 (2013), 133-144, (arXiv)
  88. R. Klén, Y. Li, M. Vuorinen: Subdomain geometry of hyperbolic type metrics. – Transactions of
    the Institute of Mathematics of the National Academy of Sciences of Ukraine,
    Vol. 10, N 4-5 (2013), 190-206. (arXiv)
  89. R. Klén, M. Vuorinen: Inclusion relations of hyperbolic type metric balls II – Publ. Math. Debrecen 83/1-2 (2013), 21-42. (arXiv)
  90. R. Klén, V. Suomala: Dimension of the boundary in different metrics – Math. Scand. 112 (2013), 275-301. (arXiv)
  91. R. Klén, M. Vuorinen: Inclusion relations of hyperbolic type metric balls – Publ. Math. Debrecen 81/3-4 (2012), 289-311. (arXiv)
  92. R. Klén, M. Vuorinen: Apollonian circles and hyperbolic geometry – J. Analysis 19 (2011), 41-60. (arXiv)
  93. E. Lankinen, A. Saraste, T. Noponen, R. Klén, M. Teräs, T. Kokki, S. Kajander, M. Pietilä, H. Ukkonen, J. Knuuti: Coronary plaque imaging in patients with unstable angina pectoris using dual gated [18F]-FDG PET/CT – Eur. Heart J. Suppl. 13 (2011), A2.
  94. R. Klén, A. Rasila, J. Talponen: Quasihyperbolic Geometry in Euclidean and Banach Spaces – J. Analysis 18 (2010), 261-278. (arXiv)
  95. R. Klén: Close-to-convexity of Quasihyperbolic and j-metric Balls – Ann. Acad. Sci. Fenn. Math. 35 (2010), 493-501. (arXiv)
  96. R. Klén, M. Visuri, M. Vuorinen: On Jordan type inequalities for hyperbolic functions – J. Inequal. Appl. Vol. 2010, Article ID 362548, 14pp. (arXiv)
  97. R. Klén, T. Noponen, J. Koikkalainen, J. Lötjönen, K. Thielemans, E. Hoppela, H. Sipilä, M. Teräs, J. Knuuti: CT based motion correction of dual gated cardiac PET images – J. Nucl. Med. 51 (2010), no. supplement 2 13672009
  98. T. Kokki, H.T. Sipilä M. Teräs, T. Noponen, N. Durand-Schaefer, R. Klén, J. Knuuti: Dual gated PET/CT imaging of small targets of the heart: Method description and testing with a dynamic heart phantom – J. Nucl. Cardiol. 17 (2009), 71-84.
  99. R. Klén: On hyperbolic type metrics – Ann. Acad. Sci. Fenn. Math. Diss. 152, 2009, 49 pp. 2008.
  100. R. Klén: Local Convexity Properties of Quasihyperbolic Balls in Punctured Space – J. Math. Anal. Appl. 342 (2008), 192-201. (arXiv)
  101. R. Klén: Local Convexity Properties of j-metric Balls – Ann. Acad. Sci. Fenn. Math. 33 (2008), 281-293. (arXiv)