Tootfinder

Contrastive Anatomy-Contrast Disentanglement: A Domain-General MRI Harmonization Method
Daniel Scholz, Ayhan Can Erdur, Robbie Holland, Viktoria Ehm, Jan C. Peeken, Benedikt Wiestler, Daniel Rueckert
https://arxiv.org/abs/2509.06592

Contrastive Anatomy-Contrast Disentanglement: A Domain-General MRI Harmonization Method
Magnetic resonance imaging (MRI) is an invaluable tool for clinical and research applications. Yet, variations in scanners and acquisition parameters cause inconsistencies in image contrast, hindering data comparability and reproducibility across datasets and clinical studies. Existing scanner harmonization methods, designed to address this challenge, face limitations, such as requiring traveling subjects or struggling to generalize to unseen domains. We propose a novel approach using a conditi…

Das hat mit dem Beutelsbacher Konsens nichts zu tun, das ist einfach nur Kulturkampf aus allen Rohren. Künftig dann statt Heinrich-Böll- oder Geschwister-Scholl-Schulen lieber Hindenburg- und Von-Papen-Gymnasien. In welchen sich die Lehrer gefälligst GAR NICHT mehr zum Thema Politik in irgendeiner Weise äußern. #FediLZ

From Diagnosis to Therapy: Progress in SPECT and PET Reconstruction for Theranostics
Kweku Enninful, Fardeen Ahmed, Bradley Girod, Richard Laforest, Daniel L. J. Thorek, Vikas Prasad, Abhinav K. Jha
https://arxiv.org/abs/2509.07313

From Diagnosis to Therapy: Progress in SPECT and PET Reconstruction for Theranostics
The theranostic paradigm enables personalization of treatment by selecting patients with a diagnostic radiopharmaceutical and monitoring therapy using a matched therapeutic isotope. This strategy relies on accurate image reconstruction of both pre-therapy and post-therapy images for patient selection and monitoring treatment. However, traditional reconstruction methods are hindered by challenges such as crosstalk in multi-isotope imaging and extremely low-count measurements when imaging of alph…

Uncertainty-Aware Deep Learning for Wildfire Danger Forecasting
Spyros Kondylatos, Gustau Camps-Valls, Ioannis Papoutsis
https://arxiv.org/abs/2509.25017 https://

Uncertainty-Aware Deep Learning for Wildfire Danger Forecasting
Wildfires are among the most severe natural hazards, posing a significant threat to both humans and natural ecosystems. The growing risk of wildfires increases the demand for forecasting models that are not only accurate but also reliable. Deep Learning (DL) has shown promise in predicting wildfire danger; however, its adoption is hindered by concerns over the reliability of its predictions, some of which stem from the lack of uncertainty quantification. To address this challenge, we present an…

The method of the approximate inverse for limited-angle CT
Bernadette Hahn, Gael Rigaud, Richard Schm\"ahl
https://arxiv.org/abs/2510.04369 https://ar…

The method of the approximate inverse for limited-angle CT
Limited-angle computerized tomography stands for one of the most difficult challenges in imaging. Although it opens the way to faster data acquisition in industry and less dangerous scans in medicine, standard approaches, such as the filtered backprojection (FBP) algorithm or the widely used total-variation functional, often produce various artefacts that hinder the diagnosis. With the rise of deep learning, many modern techniques have proven themselves successful in removing such artefacts but…

Achieving quantum-limited sub-Rayleigh identification of incoherent sources with arbitrary intensities
Danilo Triggiani, Cosmo Lupo
https://arxiv.org/abs/2509.03511 https://

Achieving quantum-limited sub-Rayleigh identification of incoherent sources with arbitrary intensities
The Rayleigh diffraction limit imposes a fundamental restriction on the resolution of direct imaging systems, hindering the identification of incoherent optical sources, such as celestial bodies in astronomy and fluorophores in bioimaging. Recent advances in quantum sensing have shown that this limit can be circumvented through spatial demultiplexing (SPADE) and photon detection. Notably, the latter is a semi-classical detection strategy, being SPADE a linear transformation of the field and pho…

Near-infrared photometry of the central stars of planetary nebulae with the VVVX survey
Dante Minniti (Instituto de Astrof\'isica, Depto. de. F\'isica y Astronom\'ia, Facultad de Ciencias Exactas, Universidad Andr\'es Bello, Santiago, Chile, Vatican Observatory, V00120 Vatican City State, Italy), Vasiliki Fragkou (Observat\'orio do Valongo, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brasil), Javier Alonso-Garc\'ia (Centro de Astronom\'ia), Danie…

Near-infrared photometry of the central stars of planetary nebulae with the VVVX survey
Achieving accurate photometric characterizations of central stars of planetary nebulae (CSPNe) toward the galactic plane is significantly hindered by the high levels of interstellar extinction in these regions. However, near-infrared (NIR) observations offer a more effective alternative, as extinction is substantially reduced at these wavelengths. By mitigating the effects of interstellar extinction via NIR observations of the Galactic disk and bulge, we seek to improve the identification and c…

kabr-tools: Automated Framework for Multi-Species Behavioral Monitoring
Jenna Kline, Maksim Kholiavchenko, Samuel Stevens, Nina van Tiel, Alison Zhong, Namrata Banerji, Alec Sheets, Sowbaranika Balasubramaniam, Isla Duporge, Matthew Thompson, Elizabeth Campolongo, Jackson Miliko, Neil Rosser, Tanya Berger-Wolf, Charles V. Stewart, Daniel I. Rubenstein
https://

kabr-tools: Automated Framework for Multi-Species Behavioral Monitoring
A comprehensive understanding of animal behavior ecology depends on scalable approaches to quantify and interpret complex, multidimensional behavioral patterns. Traditional field observations are often limited in scope, time-consuming, and labor-intensive, hindering the assessment of behavioral responses across landscapes. To address this, we present kabr-tools (Kenyan Animal Behavior Recognition Tools), an open-source package for automated multi-species behavioral monitoring. This framework in…

🇺🇦 Auf radioeins läuft...
Hinds feat. Beck:
🎵 Boom Boom Back
#NowPlaying #Hinds #Beck
https://hinds.bandcamp.com/track/boom-boom-back-ft-beck
https://open.spotify.com/track/7F23DCedR78uUiAVbY3vG1
Schon gewusst❓
Wenn Du einen Beitrag des Bots ⭐ FAVORISIERST, erfährt das nur der Bot - nicht Deine FollowerInnen.
Wenn Du einen Song weitererempfehlen möchtest, dann 🔁 TEILE ihn❗

A Drone-mounted Magnetometer System for Automatic Interference Removal and Landmine Detection
Alex Paul Hoffmann, Matthew G. Finley, Eftyhia Zesta, Mark B. Moldwin, Lauro V. Ojeda
https://arxiv.org/abs/2510.01417

A Drone-mounted Magnetometer System for Automatic Interference Removal and Landmine Detection
Landmines have been extensively used in conflict zones as an indiscriminate weapon to control military movements, often remaining active long after hostilities have ended. Their presence poses a persistent danger to civilians, hindering post-war recovery efforts, causing injuries or death, and restricting access to essential land for agriculture and infrastructure. Unmanned aerial vehicles (UAV) equipped with magnetometers are commonly used to detect remnant hidden landmines but come with signi…