output
20162026
most citedMetrics reloaded: Recommendations for image analysis validation

469 citations

52 papers

physics.med-ph2026

VQ-Wave: A physics-driven spatio-temporal deep learning approach for non-contrast-enhanced lung ventilation and perfusion MRI

Grzegorz Bauman, Pavlos Panos, Philipp Latzin +1

Purpose: To develop a robust deep learning framework for non-contrast-enhanced functional lung MRI, overcoming the limitations of spectral decomposition in the presence of physiolo…

cs.CV2026

ORGAN: Object-Centric Representation Learning using Cycle Consistent Generative Adversarial Networks

Joël Küchler, Ellen van Maren, Vaiva Vasiliauskaitė +3

Although data generation is often straightforward, extracting information from data is more difficult. Object-centric representation learning can extract information from images in…

cs.LG2025★ 1 cited

A Composable Channel-Adaptive Architecture for Seizure Classification

Francesco Carzaniga, Michael Hersche, Kaspar Schindler +1

Objective: We develop a channel-adaptive (CA) architecture that seamlessly processes multi-variate time-series with an arbitrary number of channels, and in particular intracranial…

physics.med-ph2025★ 2 cited

First Positronium Lifetime Imaging using Mn and Co with a plastic-based PET scanner

Manish Das, Sushil Sharma, Ermias Yitayew Beyene +45

Positronium Lifetime Imaging (PLI) extends positron emission tomography by using the lifetime of positronium atoms as a probe of tissue molecular architecture. In this work, we rep…

cs.AI2025★ 5 cited

A Brief History of Digital Twin Technology

Yunqi Zhang, Kuangyu Shi, Biao Li

Emerging from NASA's spacecraft simulations in the 1960s, digital twin technology has advanced through industrial adoption to spark a healthcare transformation. A digital twin is a…

q-bio.OT2025★ 2 cited

Mathematical and Computational Nuclear Oncology: Toward Optimized Radiopharmaceutical Therapy via Digital Twins

Marc Ryhiner, Yangmeihui Song, Babak Saboury +3

This article presents the general framework of theranostic digital twins (TDTs) in computational nuclear medicine, designed to support clinical decision-making and improve cancer p…