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Duelmer, F. ; Simson, W.* ; Azampour, M.F.* ; Wysocki, M.* ; Karlas, A.* ; Navab, N.*

PHOCUS: Physics-based deconvolution for ultrasound resolution enhancement.

In: (Simplifying Medical Ultrasound). Berlin [u.a.]: Springer, 2025. 35-44 (Lect. Notes Comput. Sc. ; 15186 LNCS)
DOI
Ultrasound is widely used in medical diagnostics allowing for accessible and powerful imaging but suffers from resolution limitations due to diffraction and the finite aperture of the imaging system, which restricts diagnostic use. The impulse function of an ultrasound imaging system is called the point spread function (PSF), which is convolved with the spatial distribution of reflectors in the image formation process. Recovering high-resolution reflector distributions by removing image distortions induced by the convolution process improves image clarity and detail. Conventionally, deconvolution techniques attempt to rectify the imaging system’s dependent PSF, working directly on the radio-frequency (RF) data. However, RF data is often not readily accessible. Therefore, we introduce a physics-based deconvolution process using a modeled PSF, working directly on the more commonly available B-mode images. By leveraging Implicit Neural Representations (INRs), we learn a continuous mapping from spatial locations to their respective echogenicity values, effectively compensating for the discretized image space. Our contribution consists of a novel methodology for retrieving a continuous echogenicity map directly from a B-mode image through a differentiable physics-based rendering pipeline for ultrasound resolution enhancement. We qualitatively and quantitatively evaluate our approach on synthetic data, demonstrating improvements over traditional methods in metrics such as PSNR and SSIM. Furthermore, we show qualitative enhancements on an ultrasound phantom and an in-vivo acquisition of a carotid artery.
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Publication type Article: Conference contribution
Corresponding Author
Keywords Implicit Neural Representation In Ultrasound ; Point-spread-function ; Ultrasound Deconvolution ; Ultrasound Image Formation
ISSN (print) / ISBN 0302-9743
e-ISSN 1611-3349
Conference Title Simplifying Medical Ultrasound
Journal Lecture Notes in Computer Science
Quellenangaben Volume: 15186 LNCS, Issue: , Pages: 35-44 Article Number: , Supplement: ,
Publisher Springer
Publishing Place Berlin [u.a.]
Non-patent literature Publications
Institute(s) Institute of Biological and Medical Imaging (IBMI)