PhD Thesis
2023
Onasanya, A. (2023). Designing for Neglected Tropical Diseases: Co-creating digital diagnostic devices for Low-Resource Settings [PhD, Delft University of Technology]. Delft.
Journal Articles
2023
Onasanya, A., Bengtson, M., de Goeje, L., van Engelen, J., Diehl, J.-C., & van Lieshout (2023). Developing inclusive digital health diagnostic for schistosomiasis: a need for guidance via target product profiles [Original Research]. Frontiers in Parasitology, 2.
Prosper, O., Brice, M., Michel, B., Lisette van, L., Wellington, O., Jan-Carel, D., Gleb, V., & Temitope, E. A. (2023). Two-stage automated diagnosis framework for urogenital schistosomiasis in microscopy images from low-resource settings. Journal of Medical Imaging, 10(4), 044005.
Onasanya, A., van Engelen, J., Oladunni, O., Oladepo, O., & Diehl, J. C. (2023). Social Network Analysis of the Schistosomiasis control program in two local government areas in Oyo state, Nigeria: Insights for NTD elimination plans. PLOS Neglected Tropical Diseases, 17(4), e0011266.
Onasanya, A., Bengtson, M., Agbana, T., Oladunni, O., van Engelen, J., Oladepo, O., & Diehl, J. C. (2023). Towards Inclusive Diagnostics for Neglected Tropical Diseases: User Experience of a New Digital Diagnostic Device in Low-Income Settings. Tropical Medicine and Infectious Disease, 8(3), 176.
2022
Meulah, B., Bengtson, M., Lieshout, L. V., Hokke, C. H., Kreidenweiss, A., Diehl, J. C., Adegnika, A. A., & Agbana, T. E. (2023). A review on innovative optical devices for the diagnosis of human soil-transmitted helminthiasis and schistosomiasis: from research and development to commercialization. Parasitology, 150(2), 137-149.
Samenjo, K. T., Bengtson, M., Onasanya, A., Zambrano, J. C. I., Oladunni, O., Oladepo, O., . . . Diehl, J.-C. (2022). Stakeholders’ Perspectives on the Application of New Diagnostic Devices for Urinary Schistosomiasis in Oyo State, Nigeria: A Q-Methodology Approach. Global Health: Science and Practice.
Oyibo, P., Jujjavarapu, S., Meulah, B., Agbana, T., Braakman, I., van Diepen, A., . . . Diehl, J.-C. (2022). Schistoscope: An Automated Microscope with Artificial Intelligence for Detection of Schistosoma haematobium Eggs in Resource-Limited Settings. Micromachines, 13(5).
Meulah, B., Oyibo, P., Bengtson, M., Agbana, T., Lontchi, R. A. L., Adegnika, A. A., Oyibo, W., Hokke, C. H., Diehl, J. C., & van Lieshout, L. (2022). Performance Evaluation of the Schistoscope 5.0 for (Semi-) automated Digital Detection and Quantification of Schistosoma haematobium Eggs in Urine: A Field-based Study in Nigeria. The American Journal of Tropical Medicine and Hygiene.
2021
van Grootheest, D., Agbana, T., Diehl, J.-C., van Diepen, A., Bezzubik, V., & Vdovin, G. (2021). Large volume holographic imaging for biological sample analysis. Journal of Biomedical Optics, 26(1)
2020
Onasanya, A., Keshinro, M., Oladepo, O., Van Engelen, J., & Diehl, J. C. (2020). A Stakeholder Analysis of Schistosomiasis Diagnostic Landscape in South-West Nigeria: Insights for Diagnostics Co-creation. Frontiers in Public Health, 8(697).
Van, G.-Y., Onasanya, A., van Engelen, J., Oladepo, O., & Diehl, J. C. (2020). Improving Access to Diagnostics for Schistosomiasis Case Management in Oyo State, Nigeria: Barriers and Opportunities. Diagnostics, 10(5), 328.
Agbana, T. E., Diehl, J.-C., van Pul, F., Khan, S. M., Patlan, V., Verhaegen, M., & Vdovin, G. (2018). Imaging & identification of malaria parasites using cellphone microscope with a ball lens. PLOS ONE, 13(10), e0205020.
Conference Papers
Bengtson, M., Onasanya, A., Oyibo, P., Meulah, B., Samenjo, K. T., Braakman, I., Oyibo, W., & Diehl, J. C. (2022, 8-11 Sept. 2022). A usability study of an innovative optical device for the diagnosis of schistosomiasis in Nigeria. 2022 IEEE Global Humanitarian Technology Conference (GHTC).
Agbana, T., Nijman, P., Hoeber, M., van Grootheest, D., van Diepen, A., van Lieshout, L., . . . Vdovine, G. (2020). Detection of Schistosoma haematobium using lensless imaging and flow cytometry, a proof of principle study. Paper presented at the SPIE BiOS, San Francisco. https://doi.org/10.1117/12.2545220
Heemels, A., Agbana, T., Pereira, S., Diehl, J. C., Verhaegen, M., & Vdovin, G. (2020). Effect of partial coherent illumination on Fourier ptychography. Paper presented at the SPIE BiOS, San Francisco.
Diehl, J. C., Oyibo, P., Agbana, T., Jujjavarapu, S., Van, G.-Y., Vdovin, G., & Oyibo, W. (2020). Schistoscope: Smartphone versus Raspberry Pi based low cost diagnostic device for urinary Schistosomiasis. Paper presented at the 10th IEEE Global Humanitarian Technology Conference (GHTC), Seattle, USA.
Sluiter, M., Onasanya, A., Oladepo, O., Engelen, J. M. L., Keshinro, M., Van, G.-Y., & Jan-Carel, D. (2020). Target product profiles for devices to diagnose urinary schistosomiasis in Nigeria. Paper presented at the 10th IEEE Global Humanitarian Technology Conference (GHTC), Seattle, USA.
Agbana, T., Van, G., Oladepo, O., Vdovin, G., Oyibo, W., & Diehl, J. C. (2019, 17-20 Oct. 2019). Schistoscope: Towards a locally producible smart diagnostic device for Schistosomiasis in Nigeria. Paper presented at the 2019 IEEE Global Humanitarian Technology Conference (GHTC).
Phd Dissertations
Agbana, T. (2020). Smart optics against smart parasites: Towards point-of-care optical diagnosis of malaria and urogenital schistosomiasis. (PhD). Delft University of Technology, Delft.
MSc. Thesis
Goeje, L. d. (2021). Accelerating the development of UCP-LF CAA strip readers for schistosomiasis diagnosis. (MSc.). Delft University of Technology, Delft.
Tondo, S. K. H. (2021). Q-methodology in Design: Stakeholder perspective on the context of use and application of a new diagnostic device for the diagnosis of schistosomiasis haematobium in Ibadan- Nigeria:. (MSc.). Delft University of Technology, Delft
Kleerebezem, J. (2021). The Malaria Blood Sampling System: Enhancing the quality of field prepared malaria blood smears. (MSc.). Delft University of Technology, Delft.
Driel, N. v. (2020). Automating malaria diagnosis: a machine learning approach: Erythrocyte segmentation and parasite identification in thin blood smear microscopy images using convolutional neural networks. (MSc.). Delft University of Technology, Delft.
Engelenburg, C. v. (2020). Potential enrichments in malaria diagnostics: hyperspectral imaging and group-equivariant neural networks. (MSc.). Delft University of Technology, Delft
Sluiter, M. (2020). Smart Diagnostics for Low-Resource Settings: Target product profiles for devices to diagnose urinary schistosomiasis in Nigeria. (MSc.). Delft University of Technology, Delft
Grootheest, D. N. v. (2020). Towards a single shot holographic diagnosis of Schistosmiasis haematobium. (MSc.). Delft University of Technology, Delft.
Jujjavarapu, S. (2020). Automating the Diagnosis and Quantification of Urinary Schistosomiasis. (MSc.). Delft University of Technology, Delft.
Nijman, P. (2019). Digital holography integrated with flow cytometry for detection of urinary schistosomiasis. (MSc. MSc.). Delft University of Technology, Delft.
Heemels, A. (2019). Development towards a robust low-cost Fourier Ptychographic microscope: For the detection of malaria parasites. (MSc.). Delft University of Technology, Delft.
Lambers, L. H. R. (2019). Design of a 3D printer for healthcare in Sub-Saharan Africa. (MSc.). Delft University of Technology, Delft.
Hoeboer, M. (2019). SODOS – Smart Optical Diagnostic Of Schistosomiasis. (MSc.). Delft University of Technology, Delft.
Bachelor End Project
Bent, L. v. d., Piket, M., Setjoadi, B., & Verduijn, J. (2021). Designing a cost-effective automatic rapid diagnostics test-reader. (BSc.). Delft University Technolog, Delft.
