TY - GEN
T1 - An Improved Reconstruction Technique
AU - Hjouj, Fawaz Ibrahim
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/11/9
Y1 - 2023/11/9
N2 - In this study, we introduce an enhanced algebraic reconstruction method for generating an image from its Radon transform. Our approach enhances the conventional algebraic algorithm by integrating image moments and moments derived from specific sub-images. Both theoretical analysis and experimental outcomes yield two significant observations. Firstly, this novel algorithm consistently yields highly accurate image reconstructions. Secondly, the incorporation of moments from the provided projections enriches the information available about the target image, leading to a reduction in the number of projections necessary compared to traditional reconstruction methods.
AB - In this study, we introduce an enhanced algebraic reconstruction method for generating an image from its Radon transform. Our approach enhances the conventional algebraic algorithm by integrating image moments and moments derived from specific sub-images. Both theoretical analysis and experimental outcomes yield two significant observations. Firstly, this novel algorithm consistently yields highly accurate image reconstructions. Secondly, the incorporation of moments from the provided projections enriches the information available about the target image, leading to a reduction in the number of projections necessary compared to traditional reconstruction methods.
KW - Limited Data Tomography
KW - Moments
UR - http://www.scopus.com/inward/record.url?scp=85192830989&partnerID=8YFLogxK
U2 - 10.1145/3637684.3637714
DO - 10.1145/3637684.3637714
M3 - Conference contribution
AN - SCOPUS:85192830989
T3 - ACM International Conference Proceeding Series
SP - 25
EP - 33
BT - DMIP 2023 - Proceedings of the 2023 6th International Conference on Digital Medicine and Image Processing
T2 - 6th International Conference on Digital Medicine and Image Processing, DMIP 2023
Y2 - 9 November 2023 through 12 November 2023
ER -