imaging

Topographic reference modelling of white matter hyperintensities across the adult lifespan

This paper introduces vTRM, a framework to characterize WMH spatial patterns across age and sex, revealing distinct associations with aging, vascular, and neurodegenerative processes.

NTAD: A longitudinal neuroimaging dataset of Alzheimer's disease pathology

The paper introduces a longitudinal neuroimaging dataset of Alzheimer's disease pathology, including multimodal data from patients and controls, to identify and validate novel biomarkers.

A Comparison and Validation of BIDS Apps for Preprocessing of UCB-J PET data

This study compares and validates two BIDS Apps, PETPrep and PICNIC, against in-house software for preprocessing UCB-J PET data, finding high consistency but region-dependent bias.

PhenoMe: An interactive AI framework for interpretable, microscopy-driven phenotyping

PhenoMe provides an open-source framework for analyzing microscopy images using foundation model-derived embeddings and experimental metadata to enable phenotyping and data exploration.

MillionTrees: A global benchmark for tree detection across geography, sensor, and annotation geometry

The paper introduces MillionTrees, a global benchmark dataset for airborne tree detection, showing that current models struggle to generalize across diverse data and that training on MillionTrees improves performance.

Diffusion-Based Synthetic Pretraining for Root Segmentation in Rhizotron Images

This paper generates synthetic rhizotron images using diffusion models and shows that pretraining on these images improves root segmentation performance, especially when real annotations are limited.

How Well Does Structural MRI Classify Autism? A Leakage-Free, Site-Aware and Externally Validated Machine-Learning Evaluation in Two ABIDE Cohorts

This paper evaluates the accuracy of structural MRI in classifying autism using leakage-free, site-aware, and externally validated machine learning methods across two ABIDE cohorts, finding modest performance.

Infection-related images reduce cortical edge metastability: a specification-curve analysis of a block-design fMRI study

The paper analyzes fMRI data to show that infection-related images reduce cortical edge metastability, with significant results surviving multiple corrections.

Low-pass filtering revisited: ramped phase randomization for cryo-EM map comparison and data augmentation

This paper introduces ramped phase randomization to improve cryo-EM map comparison and data augmentation by reducing fine-scale detail while preserving low-frequency content and enhancing machine learning performance.

Variability and Landmark Quality in Anatomical Co-Registration in Neuronavigation for Brain Stimulation

This study quantifies variability in anatomical landmark localization during neuronavigation, showing operator- and landmark-specific differences and the impact of marking on inter-operator agreement.

The ViRA-L (Visual Recognition Assessment-Leuven): Development, Validation, and Age Stratified Normative Characterization of a Multi-Category Visual Recognition Battery

The paper develops and validates the ViRA-L, a visual recognition battery with age-stratified norms, showing good reliability and age-related category-specific differences.

Mapping bioimage-analysis software adoption in microscopy

The paper tracks the adoption of bioimage-analysis software across 1.7 million microscopy papers from 2010 to 2025, finding increased usage and concentration on general-purpose platforms like ImageJ/Fiji.

Measuring conscious tactile perception without report: pupil, blink, and microsaccade signatures of a tactile no-report paradigm

This paper develops a no-report tactile paradigm using eye tracking to detect conscious tactile perception without behavioral reports, finding that pupil dilation and blinking distinguish perceived from unperceived stimuli.

Spectroscopy-Based Machine Learning to Predict Stem-End Rot in Avocados with the Temporal Effects

This paper predicts stem-end rot in avocados using hyperspectral data and machine learning models, finding that physics-informed neural networks outperform traditional approaches by incorporating temporal dynamics.

A single-plane electrical impedance tomography framework for integrated liver and kidney assessment

This paper evaluates a single-plane electrical impedance tomography framework for assessing liver and kidney health, finding it feasible and effective for multi-organ evaluation.

Advancing Spatial Pattern Integration in Species Distribution Modelling With Computer Vision: How Grain Size and Extent Concepts Shape Predictions of Emerging Aquatic Insects

This paper evaluates how grain size and window extent affect Deep SDMs for predicting aquatic insect distributions, finding significant performance variations with different resolutions and extents.

A human induced pluripotent stem cell-based high-throughput screening platform for teratogenicity hazard identification

Four-model hiPSC screen in 384-well imaging reached 83% accuracy (88% sensitivity, 75% specificity) on 130 scored compounds from a 146-compound reference set, scalable to hundreds of compounds monthly.

Multimodal Connectome Markers of Disruptive Behavior Problems in Youth: Distinct Patterns of Concurrent Severity and Prospective Symptom Change

The paper uses multimodal connectome data to identify patterns of functional and structural connectivity associated with disruptive behavior severity and change in youth.

Salience network expansion as a transdiagnostic neural marker for psychopathology risk in adolescence

The paper examines whether increased salience network surface area in adolescents is specific to depression or a general marker of psychopathology, finding stronger associations with overall psychopathology than depression alone.

Tau-CTFP: A connectome-informed continuous-time first-passage model for forecasting the onset of regional tau PET abnormality

This paper introduces Tau-CTFP, a model for forecasting regional tau PET abnormality onset in Alzheimer's disease using connectome-informed continuous-time first-passage modeling, achieving high precision and recall in predicting abnormality onset.

OocystMeter, a machine-learning algorithm to count and measure Plasmodium oocysts, reveals clustering patterns in the Anopheles midgut

OocystMeter automates oocyst counting and sizing in mosquito midguts, revealing clustered spatial patterns in malaria infections.

How goals shape naturalistic memories: bias in gaze and narrative recall

This study shows how induced goals shift attention during memory encoding and bias narrative recall in a naturalistic setting.

Claustrum Morphometry Reveals Spatially Heterogeneous Alterations in 22q11DS

The paper uses surface-based morphometry to analyze claustrum structure in 22q11DS, finding age-related shape changes and reduced deformation in the syndrome.

Absolute Quantification of Tissue Composition by Raman Spectroscopy

This paper introduces a method to quantify tissue composition using Raman spectroscopy, validated on cartilage with high accuracy compared to biochemical assays.

Thyra: Bridging Mass Spectrometry Imaging and SpatialData for Unified Multi-Modal Analysis

Thyra converts Mass Spectrometry Imaging data into the SpatialData format to improve interoperability and enable multi-modal spatial analysis.

Metric-driven Pre-acquisition Diagnostics for Automated Microscopy Ultraviolet Surface Excitation (MUSE)

The paper introduces a pre-acquisition quality-control framework for MUSE microscopy that uses tile-level metrics to detect and correct imaging errors before data collection.

Intrinsic Goals for Autonomous Agents: Hierarchical Exploration Captures Future Volitional Action in Drosophila

This study uses intrinsic motivation algorithms to create agents that mimic Drosophila exploration behavior and neural representations of future actions.

Ambient light color does not detectably change the transient, flight-specific DEET response of Aedes aegypti

The study reanalyzes mosquito flight data to show DEET's transient repellent effect is not influenced by ambient light color.

Fragile streak goals induce pressure responses and an inverted-U performance pattern

This paper induces pressure through a fragile streak goal in a force-control task, showing an inverted-U performance pattern and increased physiological responses, but no consistent group-level signatures of pressure effects.

golgi: an open-source graphical platform for image-to-recruitment modeling of peripheral nerve stimulation

golgi provides an open-source platform for modeling peripheral nerve stimulation, enabling image-to-recruitment analysis with a graphical interface and reproducible results.