TY - JOUR
T1 - Computational approaches in 3D quantitative phase Imaging
T2 - Current and future trends in cellular imaging
AU - Pillai, Anusha
AU - Saritha Kamath, U.
AU - Belurkar, Sushma
AU - Udupa, Karthik S.
AU - Asundi, Anand K.
AU - Patil, Ajeetkumar
N1 - Publisher Copyright:
© 2025 The Author(s)
PY - 2025/9
Y1 - 2025/9
N2 - Phase retrieval methods are essential in computational imaging, enabling high-resolution, non-invasive imaging across various fields. This review focuses on the Transport of Intensity Equation (TIE) and its role in Quantitative Phase Imaging (QPI). We compare TIE with Shack-Hartmann and Pyramid wavefront sensors, as well as iterative methods like the Gerchberg-Saxton (GS) algorithm. While iterative methods offer flexibility, TIE provides a rapid, low-cost solution, making it ideal for real-time phase recovery. Advancements in spatial light modulators (SLMs) and electrically tunable lenses (ETLs) have enhanced TIE, achieving nanometer-scale sensitivity in milliseconds. Despite challenges in clinical translation, TIE has demonstrated potential in cellular morphology analysis and dynamic studies. This review highlights key strengths, limitations, and future directions for phase retrieval in computational imaging.
AB - Phase retrieval methods are essential in computational imaging, enabling high-resolution, non-invasive imaging across various fields. This review focuses on the Transport of Intensity Equation (TIE) and its role in Quantitative Phase Imaging (QPI). We compare TIE with Shack-Hartmann and Pyramid wavefront sensors, as well as iterative methods like the Gerchberg-Saxton (GS) algorithm. While iterative methods offer flexibility, TIE provides a rapid, low-cost solution, making it ideal for real-time phase recovery. Advancements in spatial light modulators (SLMs) and electrically tunable lenses (ETLs) have enhanced TIE, achieving nanometer-scale sensitivity in milliseconds. Despite challenges in clinical translation, TIE has demonstrated potential in cellular morphology analysis and dynamic studies. This review highlights key strengths, limitations, and future directions for phase retrieval in computational imaging.
UR - https://www.scopus.com/pages/publications/105012605890
UR - https://www.scopus.com/pages/publications/105012605890#tab=citedBy
U2 - 10.1016/j.compbiomed.2025.110852
DO - 10.1016/j.compbiomed.2025.110852
M3 - Review article
AN - SCOPUS:105012605890
SN - 0010-4825
VL - 196
JO - Computers in Biology and Medicine
JF - Computers in Biology and Medicine
M1 - 110852
ER -