Volumetric Visualization of the Dermal Vasculature with Signal and Image-based Feature Extraction on a High-frequency Ultrafast Ultrasound Dataset - Bhatti, Anam; Ishii, Takuro; Lafond, Maxime; Saijo, Yoshifumi (Ultrasound in medicine & biology, 2025)
To effectively observe the complex vascular network of the skin, 3-D volumetric imaging was performed via continuous scanning of a 1-D high-frequency ultrasound array transducer. In comparison to step-wise scanning of volumetric imaging, the acquisition of ultrasonic signal with continuous scanning is faster yet synchronous with a trade-off of transducer translation noise, which impacts the filtering of flow signal and image contrast. In this study, we proposed a processing algorithm to overcome this noise and enhance the visibility of the dermal vasculature. The proposed approach involved acquiring volumetric data from the dorsum of the hand. The acquired data were segmented along the elevational direction into sections, and region-based singular value decomposition (SVD) filtering was applied to each section to extract the flow signal. Later two-step de-noising was performed based on non-local means (NLM) and top-hat (TH) morphological filters to effectively remove background noise caused by the continuous scanning. All of the processed sections were reconstructed and rendered in a volumetric viewer for 3-D representation of the vasculature. Section-wise, region-based SVD processing highlighted the presence of the vasculature in each 2-D slice. The implementation of NLM and TH filters removed the background scanning noise and significantly enhanced image quality (contrast-to-noise ratio) through 12.87 ± 1.3 dB (before NLM) to 18.91 ± 2.3 dB (after NLM) and 62.61 ± 19.2 dB (after NLM + TH). Comprehensive visualization of the dermal vasculature in a 3-D volumetric view revealed the feasibility and significance of the proposed approach. This provides an insight into the visualization of complex vasculatures in 3-D with a 1-D array transducer, thereby enhancing diagnostic techniques in skin imaging.