TY - GEN
T1 - Constructing 3D Diffusion Tensor Imaging using DICOM Files Directly and Linear Interpolation
AU - Waluyo, Maurendra Retawan
AU - Hasanah, Salsabiil
AU - Fajar, Aziz
AU - Sarno, Riyanarto
AU - Fatichah, Chastine
AU - Utomo, Andreani
AU - Sungkono, Kelly Rossa
AU - Notopuro, Francisca
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Diffusion Tensor Imaging (DTI) is a process to determine the diffusion of water molecules in the body, especially in the brain. This process can be used to extract the neural fibers in the brain. In this study, we proposed an approach for constructing three-dimensional (3D) DTI using Digital Imaging and Communications in Medicine (DICOM) files directly and linear interpolation to improve the quality of neural fibers extraction results. Based on the experimental results, the average amounts of neural fibers generated using our approach are 155534 fibers. Meanwhile, the use of Neuroimaging Informatics Technology Initiative (NIfTI) data that was widely used in recent studies resulted in an average of 117028 fibers. So that there was an increase of 38606 fibers or about 32.9%. In addition, the metadata of the DICOM file is still stored properly and can be used for further 3D image processing. The greater amounts of fibers indicate that the more complete the fibers produced and can be more helpful for doctors to check for abnormalities that may exist.
AB - Diffusion Tensor Imaging (DTI) is a process to determine the diffusion of water molecules in the body, especially in the brain. This process can be used to extract the neural fibers in the brain. In this study, we proposed an approach for constructing three-dimensional (3D) DTI using Digital Imaging and Communications in Medicine (DICOM) files directly and linear interpolation to improve the quality of neural fibers extraction results. Based on the experimental results, the average amounts of neural fibers generated using our approach are 155534 fibers. Meanwhile, the use of Neuroimaging Informatics Technology Initiative (NIfTI) data that was widely used in recent studies resulted in an average of 117028 fibers. So that there was an increase of 38606 fibers or about 32.9%. In addition, the metadata of the DICOM file is still stored properly and can be used for further 3D image processing. The greater amounts of fibers indicate that the more complete the fibers produced and can be more helpful for doctors to check for abnormalities that may exist.
KW - DICOM
KW - Diffusion Tensor Imaging
KW - Fiber Tracking
KW - Linear Interpolation
KW - NIfTI
UR - http://www.scopus.com/inward/record.url?scp=85128182671&partnerID=8YFLogxK
U2 - 10.1109/ISMODE53584.2022.9742972
DO - 10.1109/ISMODE53584.2022.9742972
M3 - Conference contribution
AN - SCOPUS:85128182671
T3 - 2021 International Seminar on Machine Learning, Optimization, and Data Science, ISMODE 2021
SP - 80
EP - 85
BT - 2021 International Seminar on Machine Learning, Optimization, and Data Science, ISMODE 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 International Seminar on Machine Learning, Optimization, and Data Science, ISMODE 2021
Y2 - 29 January 2022
ER -