Abstract
Photoacoustic (PA) imaging (or optoacoustic imaging) is a novel biomedical imaging method in biological and medical research. This modality performs morphological, functional, and molecular imaging with and without labels in both microscopic and deep tissue imaging domains. A variety of innovations have enhanced 3D PA imaging performance and thus has opened new opportunities in preclinical and clinical imaging. However, the 3D visualization tools for PA images remains a challenge. There are several commercially available software packages to visualize the generated 3D PA images. They are generally expensive, and their features are not optimized for 3D visualization of PA images. Here, we demonstrate a specialized 3D visualization software package, namely 3D Photoacoustic Visualization Studio (3D PHOVIS), specifically targeting photoacoustic data, image, and visualization processes. To support the research environment for visualization and fast processing, we incorporated 3D PHOVIS onto the MATLAB with graphical user interface and developed multi-core graphics processing unit modules for fast processing. The 3D PHOVIS includes following modules: (1) a mosaic volume generator, (2) a scan converter for optical scanning photoacoustic microscopy, (3) a skin profile estimator and depth encoder, (4) a multiplanar viewer with a navigation map, and (5) a volume renderer with a movie maker. This paper discusses the algorithms present in the software package and demonstrates their functions. In addition, the applicability of this software to ultrasound imaging and optical coherence tomography is also investigated. User manuals and application files for 3D PHOVIS are available for free on the website (www.boa-lab.com). Core functions of 3D PHOVIS are developed as a result of a summer class at POSTECH, “High-Performance Algorithm in CPU/GPU/DSP, and Computer Architecture.” We believe our 3D PHOVIS provides a unique tool to PA imaging researchers, expedites its growth, and attracts broad interests in a wide range of studies.
Highlights
Photoacoustic imaging (PAI, or optoacoustic imaging) is a biomedical imaging technique that detects ultrasound (US) signals generated via light-induced thermal expansion and relaxation of cells within tissues, called the photoacoustic (PA) effect. [1] Based on the fundamental hybrid nature, PAI has two unique competitive differentiators: (1) strong image contrast on the basis of rich intrinsic and extrinsic optical properties, and (2) deep tissue imaging capability in an optical diffusion regime providing high spatial resolution [10]
In addition to PAI, we explored the use of the 3D PHOVIS for other popular biological and medical imaging tools, such as optical coherence tomography (OCT) and US imaging
A variety of innovations have enhanced 3D PA imaging performance but ours is the first effort to enhance visualization of PA image, which is very critical for the analysis of results
Summary
Photoacoustic imaging (PAI, or optoacoustic imaging) is a biomedical imaging technique that detects ultrasound (US) signals generated via light-induced thermal expansion and relaxation of cells within tissues, called the photoacoustic (PA) effect. [1] Based on the fundamental hybrid nature, PAI has two unique competitive differentiators: (1) strong image contrast on the basis of rich intrinsic (e.g., melanin [2], DNA/RNA [3], hemoglobin [4,5,6], lipid [7], water [8], and others [9]) and extrinsic (e.g., various contrast agents) optical properties, and (2) deep tissue imaging capability in an optical diffusion regime providing high spatial resolution [10]. [1] Based on the fundamental hybrid nature, PAI has two unique competitive differentiators: (1) strong image contrast on the basis of rich intrinsic (e.g., melanin [2], DNA/RNA [3], hemoglobin [4,5,6], lipid [7], water [8], and others [9]) and extrinsic (e.g., various contrast agents) optical properties, and (2) deep tissue imaging capability in an optical diffusion regime providing high spatial resolution [10] Due to these unique features, biological applications and medical applications have been investigated in the recent decade [11,12,13,14,15]. We expect this free software package available on the website (www.boalab.com) will broadly impact the research of PAI in the field of biological and medical imaging
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