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Moritz Zaiss

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physics.med-ph Computation and Language Machine Learning Computer Vision eess.IV Quantitative Methods Sound

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preprint2026arXiv

Beating the Style Detector: Three Hours of Agentic Research on the AI-Text Arms Race

Reproducing an empirical NLP study used to take weeks. Given the released data and a modern agentic-research harness, we redo every experiment of a recent ACL\,2026 study on personal-style post-editing of LLM drafts -- and add three new ones -- with the human investigator acting only as a reviewer-in-the-loop. We reproduce all seven preregistered hypotheses and recover the paper's headline correlation between perceived self-similarity and embedding-measured self-similarity to three decimal places ($r{=}{+}0.244$, $p{<}10^{-8}$, $n{=}648$). Under a leakage-free held-out protocol, GPT-5.5 and Claude\,Opus\,4.7 close $71$--$75\,\%$ of the style gap to the same-author ceiling on $324$ paired tasks, against $24\,\%$ for the human post-edit, and beat the human post-edit on $\sim$$80\,\%$ of tasks. We then frame the same data as an AI-text detection arms race. A leave-authors-out linear SVM on LUAR-MUD embeddings reaches AUC $0.93$--$1.00$ across approaches; six diagnostics show that GPT-5.5 detection is mostly a length confound while Opus detection is a genuine stylistic signature. Given $T{=}20$ feedback iterations against the frozen detector, an Opus agent flips two of five held-out test mimics to the human half-space and shrinks every margin by an order of magnitude. With moderate effort against a known detector, a frontier LLM can already efficiently lower its own AI-detection probability. All code, $648$ mimic drafts, trained detectors, diagnostics, and adversarial trajectories are released.

preprint2026arXiv

SIREM: Speech-Informed MRI Reconstruction with Learned Sampling

Real-time magnetic resonance imaging (rtMRI) of speech production enables non-invasive visualization of dynamic vocal-tract motion and is valuable for speech science and clinical assessment. However, rtMRI is fundamentally constrained by trade-offs among spatial resolution, temporal resolution, and acquisition speed, often leading to undersampled k-space measurements and degraded reconstructions. We propose SIREM, a speech-informed MRI reconstruction framework that uses synchronized speech as a cross-modal prior. The central idea is that vocal-tract configurations during speech are correlated with the produced acoustics, making part of the image content predictable from audio. SIREM models each frame as a fusion of an audio-driven component and an MRI-driven component through a spatial weighting map. The audio branch predicts articulator-related structure from speech, while the MRI branch reconstructs complementary content from measured k-space data. We further introduce a learnable soft weighting profile over spiral arms, enabling a differentiable study of how k-space arm usage interacts with speech-informed fusion. This yields a unified multimodal formulation that combines audio-driven prediction, MRI reconstruction, and sampling adaptation. We evaluate SIREM on the USC speech rtMRI benchmark against standard baselines, including gridding, wavelet-based compressed sensing, and total variation. SIREM introduces a speech-informed reconstruction paradigm that operates in a substantially higher-throughput regime than iterative methods while preserving anatomically plausible vocal-tract structure. These results establish an initial benchmark for multimodal speech-informed rtMRI reconstruction and highlight the potential of synchronized speech as an auxiliary prior for fast reconstruction. The source code is available at https://github.com/mdhasanai/SIREM

preprint2022arXiv

snapshot CEST++ : the next snapshot CEST for fast whole-brain APTw imaging at 3T

CEST suffers from two main problems long acquisitin times or restricted coverage as well as incoherent protocol settings. In this paper we give suggestions on how to optimise your protocol settings fro CEST and present one setting for APT CEST. To increase the coverage while keeping the acquisition time constant we suggest using a spatial temporal Compressed Sensing approach. Finally, 1.8mm isotropic whole brain APT CEST maps can be acquired in a little bit less than 2min with a fully integrated online reconstruction. This will pave the way to an even further clinical use of CEST.

preprint2021arXiv

An End-to-End AI-Based Framework for Automated Discovery of CEST/MT MR Fingerprinting Acquisition Protocols and Quantitative Deep Reconstruction (AutoCEST)

Purpose: To develop an automated machine-learning-based method for the discovery of rapid and quantitative chemical exchange saturation transfer (CEST) MR fingerprinting acquisition and reconstruction protocols. Methods: An MR physics governed AI system was trained to generate optimized acquisition schedules and the corresponding quantitative reconstruction neural-network. The system (termed AutoCEST) is composed of a CEST saturation block, a spin dynamics module, and a deep reconstruction network, all differentiable and jointly connected. The method was validated using a variety of chemical exchange phantoms and an in-vivo mouse brain at 9.4T. Results: The acquisition times for AutoCEST optimized schedules ranged from 35-71s, with a quantitative image reconstruction time of only 29 ms. The resulting exchangeable proton concentration maps for the phantoms were in good agreement with the known solute concentrations for AutoCEST sequences (mean absolute error = 2.42 mM; Pearson's r=0.992 , p$<$0.0001), but not for an unoptimized sequence (mean absolute error = 65.19 mM; Pearson's r=-0.161, p=0.522). Similarly, improved exchange rate agreement was observed between AutoCEST and quantification of exchange using saturation power (QUESP) methods (mean absolute error: 35.8 Hz, Pearson's r=0.971, p$<$0.0001) compared to an unoptimized schedule and QUESP (mean absolute error = 58.2 Hz; Pearson's r=0.959, p$<$0.0001). The AutoCEST in-vivo mouse brain semi-solid proton volume-fractions were lower in the cortex (12.21$\pm$1.37%) compared to the white-matter (19.73 $\pm$ 3.30%), as expected, and the amide proton volume-fraction and exchange rates agreed with previous reports. Conclusion: AutoCEST can automatically generate optimized CEST/MT acquisition protocols that can be rapidly reconstructed into quantitative exchange parameter maps.

preprint2013arXiv

Inverse Z-spectrum analysis for MT- and spillover-corrected and T1-compensated steady-state pulsed CEST-MRI - application to pH-weighted MRI of acute stroke

Endogenous chemical exchange saturation transfer (CEST) effects are always diluted by competing effects such as direct water proton saturation (spillover) and macromolecular magnetization transfer (MT). This leads to T2-and MT-shine-through effects in the actual biochemical contrast of CEST. Therefore, a simple evaluation algorithm which corrects the CEST signal was searched for. By employing a recent eigenspace theory valid for spinlock and continuous wave (cw) CEST we predict that the inverse Z-spectrum is beneficial to Z-spectrum itself. Based on this we propose a new spillover- and MT-corrected magnetization transfer ratio (MTRRex) yielding Rex, the exchange dependent relaxation rate in the rotating frame. For verification, the amine proton exchange of creatine in solutions with different agar concentration was studied experimentally at clinical field strength of 3T. In contrast to the compared standard evaluation for pulsed CEST experiments, MTRasym, our approach shows no T2 or MT shine through effect. We demonstrate that spillover can be corrected properly and also quantitative evaluation of pH and creatine concentration is possible which proves MTRRex as quantitative CEST-MRI method. A spillover correction is of special interest for clinical static field strengths and protons resonating near the water peak. This is the case for -OH-CEST effects like gagCEST or glucoCEST, but also amine exchange of creatine or glutamate which require high B1. Although, only showed for amine exchange, we propose our normalization to work generally for DIACEST, PARACEST in slow- and fast exchange regime not just as a correction, but also for quantitative CEST-MRI. Applied to acute stroke induced in rat brain, the corrected CEST signal shows significantly higher contrast between stroke area and normal tissue as well as less B1 dependency compared to conventional approaches.

preprint2012arXiv

Exchange-dependent relaxation in the rotating frame for slow and intermediate exchange - modeling off-resonant spin-lock and chemical exchange saturation transfer

Chemical exchange observed by NMR saturation transfer (CEST) and spin-lock (SL) experiments provide an MRI contrast by indirect detection of exchanging protons. The determination of the relative concentrations and exchange rates is commonly achieved by numerical integration of the Bloch-McConnell equations. We derive an analytical solution of the Bloch-McConnell equations that describes the magnetization of coupled spin populations under radiofrequency irradiation.As CEST and off-resonant SL are equivalent, their steady-state magnetization and dynamics can be predicted by the same single eigenvalue: the longitudinal relaxation rate in the rotating frame R1rho. For the case of slowly exchanging systems, e.g. amide protons, the saturation of the small proton pool is affected by transverse relaxation (R2b). It turns out, that R2b is also significant for intermediate exchange, such as amine- or hydroxyl-exchange or paramagnetic CEST agents, if pools are only partially saturated. We propose a solution for R1rho that includes R2 of the exchanging pool by extending existing approaches, and verify it by numerical simulations. With the appropriate projection factors, we obtain an analytical solution for CEST and SL for nonzero R2 of the exchanging pool, whilst considering the dilution by direct water saturation across the entire Z-spectra. This allows the optimization of irradiation parameters and the quantification of pH-dependent exchange rates and metabolite concentrations. In addition, we propose evaluation methods that correct for concomitant direct saturation effects. It is shown that existing theoretical treatments for CEST are special cases of this approach.

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