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Updated: Feb 12, 2026
11:21
Integrated Photoacoustic Ophthalmoscopy and Spectral-domain Optical Coherence Tomography
Published on: January 15, 2013
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Fully non-linear blob basis based fluorescence photoacoustic pharmaco-kinetic tomography using non-sequential
Bharadwaj Jampu1, Naren Naik1,2, Omprakash Gottam3
1Department of Electrical Engineering, Indian Institute of Technology Kanpur, Kanpur, India.
Physics in Medicine and Biology
|February 10, 2026
Summary
This study presents the first pointwise reconstruction for fully nonlinear pharmacokinetic fluorescence photoacoustic tomography (PK-FPAT). The novel approach uses blob basis functions and an efficient sensitivity scheme, enabling scalable pharmacokinetic imaging.
Area of Science:
- Biomedical Imaging
- Computational Imaging
- Medical Physics
Background:
- Pharmacokinetic fluorescence photoacoustic tomography (PK-FPAT) is crucial for functional imaging.
- Previous methods faced challenges in pointwise reconstruction and computational efficiency.
- Developing advanced algorithms is essential for accurate pharmacokinetic modeling.
Purpose of the Study:
- To develop and validate a fully nonlinear, pointwise reconstruction method for PK-FPAT.
- To introduce an efficient computational framework for solving the PK-FPAT inverse problem.
- To demonstrate the feasibility of the proposed method using numerical simulations.
Main Methods:
- Utilized 2D-blob basis functions for object representation, reducing unknowns and improving localization.
- Employed an efficient non-sequential sensitivity scheme for evaluating two-compartment model derivatives.
- Implemented a dual-grid framework with finite element method (FEM) for forward problems and Gauss-Newton/gradient filtering for parameter reconstruction in blob basis.
Main Results:
- Achieved the first reported pointwise formulation and reconstruction for fully nonlinear PK-FPAT.
- Developed novel non-sequential sensitivity-based gradient and Gauss-Newton filter reconstruction frameworks.
- Validated the scheme on cancer-mimicking phantoms, showing good localization and correspondence to ground-truth parameters.
Conclusions:
- The proposed method offers significant computational advantages through efficient derivative evaluation and sparse parameter representation.
- This framework enables the scalability of PK-FPAT for 3D pointwise pharmacokinetic imaging.
- The study paves the way for more accurate and efficient functional imaging in real-world applications.
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