arXiv AI

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.

arXiv AI
Jul 31

PatchDenoiser: Parameter-efficient multi-scale patch learning and fusion denoiser for Low-dose CT imaging

arXiv:2602. 21987v3 Announce Type: replace-cross Abstract: Low-dose CT images are essential for reducing radiation exposure in cancer screening, pediatric imaging, and longitudinal monitoring protocols, but their quality is often degraded by noise from low-dose acquisition, patient motion, or scanner limitations, affecting both clinical interpretation and downstream analysis.

By Jitindra Fartiyal, Pedro Freire, Sergei K. Turitsyn, Sergei G. Solovski
arXiv Machine Learning
Aug 5

Assessment of Conditional Diffusion Model for Synthetic Histopathology Image Generation

arXiv:2608. 03990v1 Announce Type: new Abstract: Synthetic histopathology image generation has emerged as an approach that may address data scarcity in computational pathology, yet current evaluation methodologies may not fully assess synthetic data quality for medical applications.

By Seyed Kahaki, Shijie Li, Weijie Chen, Nicholas Petrick
arXiv AI
Jul 29

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.

By Mary John, Shibili Said, Imad Barhumi, Sherzod Turaev, Mohamed Yahia
arXiv AI
Jun 10

Deep Slice Interpolation for Reducing Through-Plane Anisotropy and Noise in Head CT

arXiv:2606. 09953v1 Announce Type: cross Abstract: Head computed tomography (CT) typically uses sub-millimeter in-plane resolution but 2-5 mm through-plane spacing, creating substantial anisotropy that degrades multiplanar reconstructions, volumetric measurements such as hematoma volume estimation, and downstream algorithms that assume near-isotropic voxels.

By Luis Cort\'es Ferre, Miguel A. Guti\'errez-Naranjo, Marcin Balcerzyk
arXiv AI
Aug 3

Dense Temporal Contrast Synthesis via Conditioned Latent Transport

arXiv:2607. 29394v1 Announce Type: cross Abstract: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is essential for breast cancer management, but reliance on gadolinium-based contrast agents (GBCAs) restricts use in contraindicated populations, prolongs scan protocols, and presents environmental toxicity concerns.

By Smriti Joshi, Apostolia Tsirikoglou, Daniel M. Lang, Richard Osuala, Noah M\'arquez Varaa, Alejandro Guzman, Grzegorz Skorupko, Sebastian Ibarra Arregui, Lidia Garrucho, Akane Ohashi, Dimitra Ntoula, Eugen Divjak, O\u{g}uz Lafc{\i}, Jan C. Peeken, Julia A. Schnabel, Fredrik Strand, Oliver Diaz, Karim Lekadir
arXiv AI
Jun 3

Anatomy-Anchored Self-Supervision: Distilling Vision Foundation Models for Invariant Ultrasound Representation

arXiv:2605. 25402v2 Announce Type: replace-cross Abstract: Self-supervised pre-training paradigm has gained increasing prominence for learning transferable representations in medical imaging, yet existing methods for ultrasound (US) images operate at the image or frame level, overlooking the anatomical context for clinical-aligned representation learning.

By Chunzheng Zhu, Yijun Wang, Jianxin Lin, Feng Wang, Hongwei Wang, Lei Zhao, Shengli Li, Kenli Li