Review
BibTex RIS Cite

Bibliometric Analysis of Diffuse Optical Tomography Studies Between 1994-2024

Year 2025, Volume: 46 Issue: 3, 435 - 446, 30.09.2025
https://doi.org/10.17776/csj.1637597

Abstract

This study covers the period 1994–2024 of bibliographic research on Diffuse Optical Tomography (DOT), using data retrieved from the Web of Science (WOS) database. The primary objective is to conduct a comprehensive bibliometric analysis of academic publications on DOT by constructing networks of authorship, sources, citations, keywords, institutions, and countries. The analysis was performed using the "Bibliometrix" package in R, supplemented by descriptive statistical methods. Over the past 30 years, the study identified key publication trends, evolving research priorities, and emerging thematic areas within the field. A total of 759 scientific documents published across 293 different sources were analyzed. The author collaboration network revealed an average of 5.39 co-authors per publication, and approximately 26% of the studies involved international collaboration. The most productive authors contributed up to 50 or more publications, while over 65% of the contributors authored only a single article. These findings highlight both concentrated research efforts by leading scholars and a wide distribution of interest among broader scientific communities.

References

  • [1] Avcı M., Modeling the Effect of Heat Distribution in Photothermal Therapy by Using Computational Fluid Dynamics (CFD), Cumhuriyet Science Journal, 45(4) (2024) 750–755.
  • [2] Erkal D. and Kuday S., Carbon Radiotheraphy for Head and Neck Cancer: Dosimetric Comparison with Photon Plans, Cumhuriyet Science Journal, 43(4) (2022) 746–751.
  • [3] Khosravi M., Yazdanshenas M., and Nemati M. H., Design of an expert system for diagnosis of thyroid cancer, Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi, 36(3) (2015) 1420–1424.
  • [4] Kumtepe T. and Doğan M., The Role of Cisplatin Loaded Biocompatible Nanoparticles in Cancer Treatment, Cumhuriyet Science Journal, 43(2) (2022) 183–187.
  • [5] Kalaiarasi A. R. and Aishwarya G. P., Microsensor for Cancer Detection and MEMS Actuator for Cancer Therapy, Transactions on Electrical and Electronic Materials, 24(1) (2023) 82–90.
  • [6] Hoshi Y. and Yamada Y., Overview of diffuse optical tomography and its clinical applications, J Biomed Opt, 21(9) (2016) 091312.
  • [7] Üncü Y. A., Sevim G., and Canpolat M., Approaches to preclinical studies with heterogeneous breast phantom using reconstruction and three-dimensional image processing algorithms for diffuse optical imaging, Int J Imaging Syst Technol, 32(1) (2022) 343–353.
  • [8] Sevim G., Üncü Y. A., and Canpolat M., Application of Reconstruction Algorithms by Simulation Experiments for the Diagnosis of Breast Tumor-Like Tissues Modeled in Diffuse Optical Tomography, Duzce University Journal of Science and Technology, 9(6) (2021) 167–176.
  • [9] Sevim G., Mercan T., Uncu Y. A., and Canpolat M., A new reconstruction technique used in Diffuse Optical Tomography System, in 2017 21st National Biomedical Engineering Meeting (BIYOMUT), Istanbul, 2017, i-iv.
  • [10] Sevim G., Üncü Y. A., Mercan T., and Canpolat M., Image reconstruction for diffuse optical tomography using bi-conjugate gradient and transpose-free quasi minimal residual algorithms and comparison of them, Int J Imaging Syst Technol, 31(4) (2021) 1894–1905.
  • [11] Üncü Y. A., Sevim G., Mercan T., Vural V., Durmaz E., and Canpolat M., Differentiation of tumoral and non-tumoral breast lesions using back reflection diffuse optical tomography: A pilot clinical study, Int J Imaging Syst Technol, 31(4) (2021) 2023–2031.
  • [12] Mercan T., Sevim G., Üncü Y. A., Uslu S., Kazancı H. Ö., and Canpolat M., The Comparison of Reconstruction Algorithms for Diffuse Optical Tomography, Süleyman Demirel University Faculty of Arts and Science Journal of Science, 14(2) (2019) 285–295.
  • [13] Boas D. A. et al., Imaging the body with diffuse optical tomography, IEEE Signal Process Mag, 18(6) (2001) 57–75.
  • [14] Burcin Unlu M., Birgul O., Shafiiha R., Gulsen G., and Nalcioglu O., Diffuse optical tomographic reconstruction using multifrequency data, J Biomed Opt, 11(5) (2006) 054008.
  • [15] Yamada Y. and Okawa S., Diffuse optical tomography: Present status and its future, Opt Rev, 21(3) (2014) 185–205.
  • [16] Bi B., Han B., Han W., Tang J., and Li L., Image reconstruction for diffuse optical tomography based on radiative transfer equation, Comput Math Methods Med, 2015 (2015).
  • [17] Sevim G., Üncü Y. A., and Canpolat M., Difüz Optik Tomografi Sistemlerinde Kullanılan Geri Çatım Algoritmaları için İterasyon Sayısını Belirmede Alternatif Bir Yöntem, Süleyman Demirel Üniversitesi Fen Edebiyat Fakültesi Fen Dergisi, 16(1) (2021) 246–258.
  • [18] Tarvainen T., Vauhkonen M., and Arridge S. R., Gauss–Newton reconstruction method for optical tomography using the finite element solution of the radiative transfer equation, J Quant Spectrosc Radiat Transf, 109(17) (2008) 2767–2778.
  • [19] Tarvainen T., Vauhkonen M., Kolehmainen V., Arridge S. R., and Kaipio J. P., Coupled radiative transfer equation and diffusion approximation model for photon migration in turbid medium with low-scattering and non-scattering regions, Phys Med Biol, 50(20) (2005) 4913–4930.
  • [20]Mozumder M., Hauptmann A., Nissila I., Arridge S. R., and Tarvainen T., A Model-Based Iterative Learning Approach for Diffuse Optical Tomography, IEEE Trans Med Imaging, 41(5) (2022) 1289–1299.
  • [21] Arridge S. R. et al., Approximation errors and model reduction with an application in optical diffusion tomography, Inverse Probl, 22(1) (2006) 175.
  • [22] Gunther J. E. et al., Dynamic Diffuse Optical Tomography for Monitoring Neoadjuvant Chemotherapy in Patients with Breast Cancer, Radiology, 287(3) (2018) 778–786.
  • [23]Culver J. P., Durduran T., Furuya D., Cheung C., Greenberg J. H., and Yodh A. G., Diffuse optical tomography of cerebral blood flow, oxygenation, and metabolism in rat during focal ischemia, J Cereb Blood Flow Metab, 23(8) (2003) 911–924.
  • [24]Lee C. W., Cooper R. J., and Austin T., Diffuse optical tomography to investigate the newborn brain, Pediatr Res, 82(3) (2017) 376–386.
  • [25]Singh H. et al., Mapping cortical haemodynamics during neonatal seizures using diffuse optical tomography: A case study, Neuroimage Clin, 5 (2014) 256–265.
  • [26]Ahbbinaya V. and Jeeva J. B., Diffuse Optical Tomographic imaging using NIR Camera, 13th International Conference on Fiber Optics and Photonics, Kanpur India, 2016, W3A.17.
  • [27] Zhao, H., Gao, F., Tanikawa, Y., & Yamada, Y., Theoretical and experimental study on near infrared time-resolved optical diffuse tomography. In Saratov Fall Meeting 2005: Optical Technologies in Biophysics and Medicine VII (SPIE), 6163 (2006) 136-145.
  • [28]Sabir S. et al., Convolutional neural network-based approach to estimate bulk optical properties in diffuse optical tomography, Appl Opt, 59(5) (2020) 1461.
  • [29]Mering M., In Lay Terms: Bibliometrics: Understanding Author-, Article- and Journal- Level Metrics, Serials Review, 43 (2017) 0.
  • [30]Andrés A., Measuring Academic Research: How to Undertake a Bibliometric Study. 2009.
  • [31] S. Bolat et al., ‘A Bibliometric and Visual Analysis of Publications on Low-Density Lipoprotein Cholesterol Estimating Equations’, Cumhuriyet Science Journal, vol. 45, no. 4, pp. 648–657, Dec. 2024, doi: 10.17776/CSJ.1452125.
  • [32]L. Bornmann and H. D. Daniel, ‘What do citation counts measure? A review of studies on citing behavior’, Journal of Documentation, vol. 64, no. 1, pp. 45–80, 2008, doi: 10.1108/00220410810844150/FULL/PDF.
  • [33]Lawani S. M., Bibliometrics: Its Theoretical Foundations, Methods and Applications, 31 (1981) 294–315.
  • [34]Martin B., What can bibliometrics tell us about changes in the mode of knowledge production?, Prometheus, 29 (2011) 455–479.
  • [35]Aria M. and Cuccurullo C., bibliometrix: An R-tool for comprehensive science mapping analysis, J Informetr, 11(4) (2017) 959–975.
  • [36]Neuhaus C. and Daniel H.D., Data Sources for Performing Citation Analysis: An Overview, Journal of Documentation, 64 (2008) 193–210.
  • [37] McLean M., RefManageR: Import and Manage BibTeX and BibLaTeX References in R, The Journal of Open Source Software, 2 (2017).
  • [38]Kawamura M., Thomas C. D. L., Tsurumoto A., Sasahara H., and Kawaguchi Y., Lotka’s law and productivity index of authors in a scientific journal, J Oral Sci, 42(2) (2000) 75–78.
  • [39]Kobayashi H., Ogawa M., Alford R., Choyke P. L., and Urano Y., New strategies for fluorescent probe design in medical diagnostic imaging, Chem Rev, 110(5) (2010) 2620–2640.
  • [40]Lu G. and Fei B., Medical hyperspectral imaging: a review, J Biomed Opt, 19(1) (2014) 010901.
  • [41] Scholkmann F. et al., A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology, Neuroimage, 85 (2014) 6–27.
  • [42]Graves E. E., Ripoll J., Weissleder R., and Ntziachristos V., A submillimeter resolution fluorescence molecular imaging system for small animal imaging, Med Phys, 30(5) (2003) 901–911.
  • [43]Soubret A., Ripoll J., and Ntziachristos V., Accuracy of fluorescent tomography in the presence of heterogeneities: study of the normalized Born ratio, IEEE Trans Med Imaging, 24(10) (2005) 1377–1386.
  • [44]Ntziachristos V., Fluorescence molecular imaging, Annu Rev Biomed Eng, 8 (2006) 1–33.
There are 44 citations in total.

Details

Primary Language English
Subjects Classical and Physical Optics, Statistical Data Science
Journal Section Natural Sciences
Authors

Yiğit Ali Üncü 0000-0001-7398-9540

Hasan Özdoğan 0000-0001-6127-9680

Gençay Sevim 0000-0002-2157-3209

Publication Date September 30, 2025
Submission Date February 11, 2025
Acceptance Date September 10, 2025
Published in Issue Year 2025 Volume: 46 Issue: 3

Cite

APA Üncü, Y. A., Özdoğan, H., & Sevim, G. (2025). Bibliometric Analysis of Diffuse Optical Tomography Studies Between 1994-2024. Cumhuriyet Science Journal, 46(3), 435-446. https://doi.org/10.17776/csj.1637597