14 papers · ranked by Valyu relevance
Lea Waller, Susanne Erk, Elena Pozzi, Yara J. Toenders + 7 more
The reproducibility crisis in neuroimaging has led to an increased demand for standardized data processing workflows. Within the ENIGMA consortium, we developed HALFpipe (Harmonized AnaLysis of Functional MRI pipeline), an open-source, containerized, user-friendly tool that facilitates reproducible analysis of…
Gail McConnell
Microscopy datasets are often spatially sparse, wherein relevant structures occupy only a small fraction of the total field of view (FOV), leaving large regions of background devoid of signal. This inherent inefficiency creates file sizes that are larger than needed, which increases the time needed for computational…
Lara Dular, Franjo Pernuš, Žiga Špiclin
Brain age is an estimate of chronological age obtained from T1-weighted magnetic resonance images (T1w MRI) and represents a simple diagnostic biomarker of brain ageing and associated diseases. While the current best accuracy of brain age predictions on T1w MRIs of healthy subjects ranges from two to three years…
Gabriel Desrosiers-Gregoire, Gabriel A. Devenyi, Joanes Grandjean, M. Mallar Chakravarty
Functional magnetic resonance imaging (fMRI) in rodents holds great potential for advancing our understanding of brain networks. Unlike the human fMRI community, there remains no standardized resource in rodents for image processing, analysis and quality control, posing significant reproducibility limitations. Our…
Jaap de Ruyter van Steveninck, Umut Güçlü, Richard van Wezel, Marcel van Gerven
Neural prosthetics may provide a promising solution to restore visual perception in some forms of blindness. The restored prosthetic percept is rudimentary compared to normal vision and can be optimized with a variety of image preprocessing techniques to maximize relevant information transfer. Extracting the most…
Xingyu Liu, Yijun Zhang, Zi Yin, Zonglei Zhen + 1 more
Macaque MRI bridges non-invasive systems neuroscience with cellular and circuit-level mechanisms, but preprocessing tools remain difficult to integrate and deploy reproducibly. We present Brainana, an automated, BIDS-compatible preprocessing and visualization framework for macaque neuroimaging. Brainana integrates…
Oscar Esteban, Christopher J. Markiewicz, Ross W. Blair, Craig A. Moodie + 12 more
Preprocessing of functional MRI (fMRI) involves numerous steps to clean and standardize data before statistical analysis. Generally, researchers create ad hoc preprocessing workflows for each new dataset, building upon a large inventory of tools available for each step. The complexity of these workflows has snowballed…
A. M. Sequeira, M. E. Ijsselsteijn, M. Rocha, Noel F.C.C. de Miranda
Multiplex spatial proteomic methodologies can provide a unique perspective on the molecular and cellular composition of complex biological systems. Several challenges are associated to the analysis of imaging data, in particular regarding the normalization of signal-to-noise ratios across images and background noise…
Jeffrey C. Berry, Noah Fahlgren, Alexandria A. Pokorny, Rebecca Bart + 1 more
High-throughput phenotyping has emerged as a powerful method for studying plant biology. Large image-based datasets are generated and analyzed with automated image analysis pipelines. A major challenge associated with these analyses is variation in image quality that can inadvertently bias results. Images are made up…
Bevan L. Cheeseman, Ulrik Günther, Mateusz Susik, Krzysztof Gonciarz + 1 more
Modern microscopy modalities create a data deluge with gigabytes of data generated each second, or terabytes per day. Storing and processing these data is a severe bottleneck. We argue that this is an artifact of the images being represented on pixels. To address the root of the problem, we here propose the Adaptive…
Mauro Silberberg, Hernán E. Grecco
Quantitative analysis of high-throughput microscopy images requires robust automated algorithms. Background estimation is usually the first step and has an impact on all subsequent analysis, in particular for foreground detection and calculation of ratiometric quantities. Most methods recover only a single background…
Sawayama Masataka
This perspective on efficient color processing is based on three key findings from material perception studies. The first finding is that color and luminance are highly redundant in certain materials, particularly in wet or translucent objects with subsurface scattering . For example, there is a strong negative…
Shu Wang, Xiaoxiang Liu, Yueying Li, Xinquan Sun + 11 more
The stitched fluorescence microscope images inevitably exist in various types of stripes or artifacts caused by uncertain factors such as optical devices or specimens, which severely affects the image quality and downstream quantitative analysis. In this paper, we present a deep learning-based Stripe Self-Correction…
Ingo Fruend
The first steps of visual processing are often described as a bank of oriented filters followed by divisive normalization. This approach has been tremendously successful at predicting contrast thresholds in simple visual displays. However, it is unclear to what extent this kind of architecture also supports processing…