The Use of Image Processing and Analysis in Automated Biological Dosimetry

Main Authors: Ramadhani, D.; Doctoral Program for Biomedical Sciences, Faculty of Medicine, Universitas Indonesia (UI), Jakarta, Indonesia, Jl. Salemba Raya 6, Jakarta 10430, Indonesia Center for Technology of Safety and Radiation Metrology, National Nuclear Energy Agency (BATAN), Jl. Lebak Bulus Raya No. 49, Jakarta 12070, Indonesia, Syaifudin, M.; Center for Technology of Safety and Radiation Metrology, National Nuclear Energy Agency (BATAN), Jl. Lebak Bulus Raya No. 49, Jakarta 12070, Indonesia, Purnami, S.; Center for Technology of Safety and Radiation Metrology, National Nuclear Energy Agency (BATAN), Jl. Lebak Bulus Raya No. 49, Jakarta 12070, Indonesia, Naroeni, A.; Virology and Cancer Pathobiology Research Center, Faculty of Medicine, Universitas Indonesia (UI), Jakarta, Indonesia, Jl. Salemba Raya 4, Jakarta 10430, Indonesia
Other Authors: Ministry of Research, Technology and Higher Education of the Republic Indonesia
Format: Article info application/pdf eJournal
Bahasa: eng
Terbitan: PPIKSN-BATAN , 2020
Subjects:
Online Access: http://aij.batan.go.id/index.php/aij/article/view/960
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Daftar Isi:
  • Biological dosimetry based on cytogenetic markers such as dicentric chromosome (DC) and micronuclei (MN) is, until now, the most frequently used method to estimate the radiation dose in the radiological accident event. Another biomarker that recently gains popularity in biodosimetry is γH2AX. All these three assays are microscope-based biodosimetry techniques, and therefore need manual scoring to estimate the radiation dose. Unfortunately, the manual scoring of these assays is time-consuming and labor-intensive. In the case of a large-scale radiological accident when many people are exposed to radiation, it is very useful to use image processing and analysis in the scoring process to obtain a faster result. Several commercial systems or open-source image processing software packages already developed automated scoring of DC, MN, and γH2AX assays. This article describes how image processing and analysis were applied in automated biodosimetry based on the DC, MN, and γH2AX assays.