arXiv AI July 29, 2026 By Mary John, Shibili Said, Imad Barhumi, Sherzod Turaev, Mohamed Yahia

Matrix-Free Photoacoustic Image Reconstruction via Sensor-Token Self-Attention

arXiv:2607. 25576v1 Announce Type: new Abstract: Photoacoustic tomography (PAT) combines the optical absorption contrast of biological tissue with the spatial resolution of ultrasound, yet recovering the initial pressure distribution from sparse-view sensor measurements remains an ill-posed inverse problem.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv AI

Jun 6

Three-Dimensional Retinal Microvasculature Restoration in OCT Angiography

arXiv:2606. 05375v1 Announce Type: cross Abstract: Optical coherence tomographic angiography (OCTA) is a powerful technique for imaging retinal microvasculature.

By Yukun Guo, Min Gao, Tristan T. Hormel, Steven T. Bailey, Thomas S. Hwang, Yali Jia

arXiv AI

Jun 18

Pyramid Self-Contrastive Learning for Single-shot Test-time Ultrasound Image Denoising

arXiv:2605. 12567v2 Announce Type: replace-cross Abstract: The inherent electronic and speckle noise complicates clinical interpretation of ultrasound images.

By Jiajing Zhang, Bingze Dai, Xi Zhang, Yue Xu, Wei-Ning Lee

arXiv AI

Jul 20

Unsupervised Deep Learning for Inverse Problems in Computed Tomography

arXiv:2508. 05321v4 Announce Type: replace-cross Abstract: Assume you encounter an inverse problem that shall be solved for a large number of data, but no ground-truth data is available.

By Laura Hellwege, Johann Christopher Engster, Moritz Schaar, Thorsten M. Buzug, Maik Stille

benchmarks

arXiv Machine Learning

Aug 3

Few-shot Deep Learning for Phase-Amplitude Aberration Correction in Transcranial Focused Ultrasound

arXiv:2607. 29182v1 Announce Type: cross Abstract: Transcranial focused ultrasound (tFUS) is a non-invasive technique that delivers focused acoustic energy through the skull for neuromodulation and therapeutic applications.

By Minju Seol, Minjee Seo, Seonaeng Cho, Kyungho Yoon

fine-tuning safety

arXiv AI

Jun 2

Flow-Based Generative Modeling for Optimizing Sampling Policies in Compressed Sensing Applications

arXiv:2606. 00078v1 Announce Type: cross Abstract: Numerous modern applications in signal processing and medical imaging necessitate acquiring high-dimensional signals under tight resource constraints.

By Roman Pavelkin, Luis A. Zavala-Mondragon, Christiaan G. A. Viviers, Fons van der Sommen

diffusion computer-vision benchmarks

arXiv Machine Learning

Jun 3

Correcting Neural Operator Spectral Bias via Diffusion Posterior Sampling with Sparse Observations

arXiv:2606. 03936v1 Announce Type: new Abstract: Neural operator surrogates (NO) approximate PDE solutions orders of magnitude faster than numerical solvers, but suffer from spectral bias: high-frequency content is systematically attenuated, limiting reliability where fine-scale structure matters.

By Niccol\`o Perrone, Fanny Lehmann, Stefania Fresca, Filippo Gatti

diffusion safety

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