Journal: Sensors (Basel, Switzerland)

Article Title: An Automatic Unmixing Approach to Detect Tissue Chromophores from Multispectral Photoacoustic Imaging

doi: 10.3390/s20113235

Figure Lengend Snippet: ( a ) Schematic representation of the simulated multispectral photoacoustic (PA) images with six inclusions, ( b ) ideal spectral curves of the inclusions.

Article Snippet: In addition to the simulation studies, experiments were performed by using Vevo LAZR-X photoacoustic image technology (FUJIFILM VisualSonics, Inc., Toronto, ON, Canada), as described elsewhere [ ].

Techniques:

Journal: Sensors (Basel, Switzerland)

Article Title: An Automatic Unmixing Approach to Detect Tissue Chromophores from Multispectral Photoacoustic Imaging

doi: 10.3390/s20113235

Figure Lengend Snippet: Pre-injection conditions: ( a ) ultrasound (US) image of the kidney–spleen view; respectively ( b ) photoacoustic (PA) image obtained at 880nm, and ( c ) S O 2 map.

Article Snippet: In addition to the simulation studies, experiments were performed by using Vevo LAZR-X photoacoustic image technology (FUJIFILM VisualSonics, Inc., Toronto, ON, Canada), as described elsewhere [ ].

Techniques: Injection

Journal: Journal of Biomedical Optics

Article Title: Multidomain computational modeling of photoacoustic imaging: verification, validation, and image quality prediction

doi: 10.1117/1.jbo.24.12.121910

Figure Lengend Snippet: Fig. 4 Reconstructed photoacoustic images of filament phantom (phantom 2) for (a) simulated and (b) experimental RF data and (c) computed axial and (d) lateral resolution from simulated and exper- imental data. The color bar is in dB.

Article Snippet: MC has been used to compare performances of different PAI device designs,20,34–41 to evaluate target lesion visualization and detectability,39,42 and to enable quantitative PAI.43,44 Common tools for modeling acoustic wave propagation in tissue include Field II,45 which has been used to simulate photoacoustic response and quantify spatial resolution of a proposed PAI system,46,47 and k-Wave,48,49 a popular open-source photoacoustic simulation toolbox for MATLAB used by several groups to study PAI systems.42,43 For PAI simulation, several groups have proposed multidomain finite element models based on commercial software (e.g., COMSOL)50,51 or open-source packages (e.g., ONELAB)52 to simulate photoacoustic processes by explicitly modeling heat transfer, solid mechanics, and acoustic wave propagation.

Techniques:

Journal: Journal of Biomedical Optics

Article Title: Multidomain computational modeling of photoacoustic imaging: verification, validation, and image quality prediction

doi: 10.1117/1.jbo.24.12.121910

Figure Lengend Snippet: Fig. 5 Upper row: Reconstructed photoacoustic images from penetration depth phantom (phantom 3) for (a) and (b) low-absorbing and (c) and (d) medium-absorbing background, using (a) and (c) experimental and (b)–(d) simulated data. Data are normalized to the intensity of the shallowest target intensity. The color bar is in dB. Lower row: line plot across second target (white line in a) for depth of 5 to 20 mm.

Article Snippet: MC has been used to compare performances of different PAI device designs,20,34–41 to evaluate target lesion visualization and detectability,39,42 and to enable quantitative PAI.43,44 Common tools for modeling acoustic wave propagation in tissue include Field II,45 which has been used to simulate photoacoustic response and quantify spatial resolution of a proposed PAI system,46,47 and k-Wave,48,49 a popular open-source photoacoustic simulation toolbox for MATLAB used by several groups to study PAI systems.42,43 For PAI simulation, several groups have proposed multidomain finite element models based on commercial software (e.g., COMSOL)50,51 or open-source packages (e.g., ONELAB)52 to simulate photoacoustic processes by explicitly modeling heat transfer, solid mechanics, and acoustic wave propagation.

Techniques:

Journal: Journal of Biomedical Optics

Article Title: Multidomain computational modeling of photoacoustic imaging: verification, validation, and image quality prediction

doi: 10.1117/1.jbo.24.12.121910

Figure Lengend Snippet: Fig. 7 Energy deposition maps and corresponding simulated photo- acoustic images for (a) and (b) 0.8- and 12.6-mm circular beams and (c) and (d) elliptical beams of size 0.25 mm × 2.5 mm and 4 mm × 40 mm. The small lower-right figure in each energy deposi- tion map is an en face view of beam fluence at the phantom surface, which were self-normalized for visualization purposes. All beam cases used a fixed uniform radiant exposure of 10 mJ∕cm2. Energy deposition colorbars in mJ∕cm3, photoacoustic image colorbars in dB.

Article Snippet: MC has been used to compare performances of different PAI device designs,20,34–41 to evaluate target lesion visualization and detectability,39,42 and to enable quantitative PAI.43,44 Common tools for modeling acoustic wave propagation in tissue include Field II,45 which has been used to simulate photoacoustic response and quantify spatial resolution of a proposed PAI system,46,47 and k-Wave,48,49 a popular open-source photoacoustic simulation toolbox for MATLAB used by several groups to study PAI systems.42,43 For PAI simulation, several groups have proposed multidomain finite element models based on commercial software (e.g., COMSOL)50,51 or open-source packages (e.g., ONELAB)52 to simulate photoacoustic processes by explicitly modeling heat transfer, solid mechanics, and acoustic wave propagation.

Techniques:

Journal: Journal of Biomedical Optics

Article Title: Multidomain computational modeling of photoacoustic imaging: verification, validation, and image quality prediction

doi: 10.1117/1.jbo.24.12.121910

Figure Lengend Snippet: Fig. 9 Reconstructed photoacoustic images of filament phantom (phantom 2) using ultrasound trans- ducer arrays with varying center frequency (columns) as well as fractional bandwidth of 50% (top row) and 100% (bottom row). Each image was normalized to its maximum target intensity.

Article Snippet: MC has been used to compare performances of different PAI device designs,20,34–41 to evaluate target lesion visualization and detectability,39,42 and to enable quantitative PAI.43,44 Common tools for modeling acoustic wave propagation in tissue include Field II,45 which has been used to simulate photoacoustic response and quantify spatial resolution of a proposed PAI system,46,47 and k-Wave,48,49 a popular open-source photoacoustic simulation toolbox for MATLAB used by several groups to study PAI systems.42,43 For PAI simulation, several groups have proposed multidomain finite element models based on commercial software (e.g., COMSOL)50,51 or open-source packages (e.g., ONELAB)52 to simulate photoacoustic processes by explicitly modeling heat transfer, solid mechanics, and acoustic wave propagation.

Techniques: