Dr. Ipek Özdemir Profile

Dr. Ipek Özdemir

at Johns Hopkins University

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Author

Publications (2)

SPIE Journal Paper | 2 June 2020

Multiscale and morphological analysis of microvascular patterns depicted in contrast-enhanced ultrasound images

Ipek Özdemir, Jun Peng, Debabrata Ghosh, Shashank Sirsi, Chieko Mineo, Philip Shaul, Kenneth Hoyt

JMI, Vol. 7, Issue 03, 034001, (June 2020) https://doi.org/10.1117/12.10.1117/1.JMI.7.3.034001

KEYWORDS: Image processing, Tissues, Morphological analysis, Ultrasonography, Glucose, Resistance, Transducers, Image analysis, Image filtering, Blood

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Proceedings Article | 15 March 2019 Presentation + Paper

Morphological image processing for multiscale analysis of super-resolution ultrasound images of tissue microvascular networks

Ipek Özdemir, Kenneth Hoyt

Proceedings Volume 10955, 1095505 (2019) https://doi.org/10.1117/12.2511974

KEYWORDS: Image processing, Image enhancement, Tissues, Ultrasonography, Image analysis, Super resolution, Analytical research, Image segmentation, In vivo imaging, Image filtering

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Diabetes is a major disease and known to impair microvascular recruitment due to insulin resistance. Previous quantifications of the changes in microvascular networks at the capillary level were being performed with either full or manually selected region-of-interests (ROIs) from super-resolution ultrasound (SR-US) images. However, these approaches were imprecise, time-consuming, and unsuitable for automated processes. Here we provided a custom software solution for automated multiscale analysis of SR-US images of tissue microvascularity patterns. An Acuson Sequoia 512 ultrasound (US) scanner equipped with a 15L8-S linear array transducer was used in a nonlinear imaging mode to collect all data. C57BL/6J male mice fed standard chow and studied at age 13-16 wk comprised the lean group (N = 14), and 24-31 wk-old mice who received a high-fat diet provided the obese group (N = 8). After administration of a microbubble (MB) contrast agent, the proximal hindlimb adductor muscle of each animal was imaged (dynamic contrast-enhanced US, DCE-US) for 10 min at baseline and again at 1 h and towards the end of a 2 h hyperinsulinemiceuglycemic clamp. Vascular structures were enhanced with a multiscale vessel enhancement filter and binary vessel segments were delineated using Otsu’s global threshold method. We then computed vessel diameters by employing morphological image processing methods for quantitative analysis. Our custom software enabled automated multiscale image examination by defining a diameter threshold to limit the analysis at the capillary level. Longitudinal changes in AUC, I_PK, and MVD were significant for lean group (p < 0.02 using Full-ROI and p < 0.01 using 150 μm-ROI) and for obese group (p < 0.02 using Full-ROI, p < 0.03 using 150 μm-ROI). By eliminating large vessels from the ROI (above 150 μm in diameter), perfusion parameters were more sensitive to changes exhibited by the smaller vessels, that are known to be more impacted by disease and treatment.

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