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Image Provenance Analysis at Scale [article]

Daniel Moreira, Aparna Bharati, Joel Brogan, Allan Pinto, Michael Parowski, Kevin W. Bowyer, Patrick J. Flynn, Anderson Rocha, Walter J. Scheirer
2018 arXiv   pre-print
This article presents an end-to-end processing pipeline for image provenance analysis, which works at real-world scale.  ...  This is a problem that recently has received the name of image provenance analysis.  ...  In addition, making such a solution perform at scale at inference time is also challenging.  ... 
arXiv:1801.06510v2 fatcat:7bvxyjw5ybawvobijrsazfqfle

EAGER: Collaborative 3D Materials Science Research in the Cloud

B.S. Manjunath
2017 Figshare  
BisQue allows management, analysis, and sharing of images and metadata for large-scale problems.  ...  BisQue (Bio Semantic Query User Environment) is a cloud-based analysis platform developed in the Center for Bio-Image Informatics at UCSB.  ...  BisQue Overview • BisQue (Bio Semantic Query User Environment) is a cloud-based analysis platform developed in the Center for Bio-Image Informatics at UCSB [KVI2010] • Allows management, analysis  ... 
doi:10.6084/m9.figshare.4652710 fatcat:gm5mcooorbcolhz77iziu2ng2q

CSSI Element : Large-Scale Image Processing Infrastructure Development (LIMPID)

B.S. Manjunath, Tresa Pollock, Amit Chowdhury, Nirav Merchant, Robert Miller, Amil Khan, Satish Kumar, Michael Goebel, Jiaxiang Jiang, Connor Levenson, Chandrakanth Gudavalli
2022 Zenodo  
This is the poster for presentation at the CSSI PI meeting on July 25-26.  ...  tasks over images and metadata • Web based provenance viewer to explore past analysis run for improved repeatability • Visit BisQue SaaS at bisque2.ece.ucsb.edu and at CyVerse bisque.cyverse.org • GitHub  ...  the web browser • Multi-modal search and mining in the datasets CSSI Element : Large-Scale Image Processing Infrastructure Development (LIMPID) Materials Dream.3D workflow in BisQue NSF CSSI PI Meeting  ... 
doi:10.5281/zenodo.6859543 fatcat:46j43inrs5fnfm4prhae5qesqu

Bisque: Advances in Bioimage Databases

Kristian Kvilekval, Dmitry Fedorov, Utkarsh Gaur, Steve Goff, Nirav Merchant, B. S. Manjunath, Ambuj K. Singh
2012 IEEE Data Engineering Bulletin  
high-throughput and large-scale image analysis using cluster/cloud resources; (iii) Strategies for managing uncertainty in measurement and analysis so that important aspects of the data are not prematurely  ...  As these collections have grown using advanced (and automated) imaging tools and microscopes, scientists need high-throughput large-scale statistical analysis of the data.  ...  Future: Coping with Uncertainty Imaging is at the core of many scientific discoveries, at scales varying from nano to astronomical observations.  ... 
dblp:journals/debu/KvilekvalFGGMMS12 fatcat:xi756bkvwvab7p32x7nhz6hhke

Beyond Pixels: Image Provenance Analysis Leveraging Metadata [article]

Aparna Bharati, Daniel Moreira, Joel Brogan, Patricia Hale, Kevin W. Bowyer, Patrick J. Flynn, Anderson Rocha, Walter J. Scheirer
2019 arXiv   pre-print
Most current works seek to build provenance graphs based on the shared content between images or videos.  ...  Provenance analysis provides a snapshot of the chronology and validity of content as it is uploaded, re-uploaded, and modified over time.  ...  Proposed Approach Image provenance analysis algorithms aim at constructing a provenance graph with related images, given a query image.  ... 
arXiv:1807.03376v3 fatcat:pvk6eqd24zfwzjnh55ri4gfdvu

The National Alliance for Medical Imaging Computing (NA-MIC)

R. Kikinis
2005 2005 IEEE Computational Systems Bioinformatics Conference (CSB'05)  
The overall analysis will occur at a range of scales, and will occur across a range of modalities including diffusion MRI, quantitative EGG, and metabolic and receptor PET, but potentially including microscopic  ...  tools for the analysis and visualization of medical image data.  ...  The overall analysis will occur at a range of scales, and will occur across a range of modalities including diffusion MRI, quantitative EGG, and metabolic and receptor PET, but potentially including microscopic  ... 
doi:10.1109/csb.2005.51 dblp:conf/csb/Kikinis05 fatcat:2q5rq3vvebekdal4m7ozfaiwtm

Multi-modal SEM Imaging for Shale Reservoir Characterization

Lori A. Hathon, Michael T. Myers, Mike Dixon, Kultaransingh Hooghan
2017 Microscopy and Microanalysis  
As we have begun to investigate geomaterials at resolutions on the single nanometer scale, our observations have upended several long-lived paradigms of geoscience.  ...  Robust segmentation of porosity, however, has not proven to be simple.  ...  Robust segmentation of porosity, however, has not proven to be simple.  ... 
doi:10.1017/s1431927617011242 fatcat:uabe4h4rkfcjvbrkbdhzrskq4e

Provenance in neuroimaging

Allan J. MacKenzie-Graham, John D. Van Horn, Roger P. Woods, Karen L. Crawford, Arthur W. Toga
2008 NeuroImage  
provenance.  ...  Knowledge about the origin and history of an image is crucial for establishing data and results quality; detailed information about how it was processed, including the specific software routines and operating  ...  The scale is 10 5 voxels. C, The result of an independent components analysis of a series of BOLD functional MRI brain images using workflow B.  ... 
doi:10.1016/j.neuroimage.2008.04.186 pmid:18519166 pmcid:PMC2664747 fatcat:ue56gsjx7bgqnk7dx4lfiky444

Position Paper: Provenance Data Visualisation for Neuroimaging Analysis [article]

Bilal Arshad, Kamran Munir, Richard McClatchey, Saad Liaquat
2015 arXiv   pre-print
neuroimaging analysis.  ...  Systems are required that offer provenance data capture and visualisation support for analyses.  ...  At each stage in the execution of the workflow, the intermediary images or data are stored and a full provenance track is kept.  ... 
arXiv:1502.01556v1 fatcat:t44kjzyiobhond67kn76ezvs7y

Nano-analysis of the Metallic Multilayers Using High Resolution Microscopy

A Genç, R Banerjee, J Ringnalda, DM Maher, HL Fraser
2006 Microscopy and Microanalysis  
HAADF-STEM is a proven technique where the images are directly interpretable due to the incoherent nature of the imaging process [5].  ...  At high enough scattering angles the intensity variations in the image is atomic number dependent (Z-Contrast).  ...  HAADF-STEM is a proven technique where the images are directly interpretable due to the incoherent nature of the imaging process [5] .  ... 
doi:10.1017/s1431927606067523 fatcat:rdeebdevs5c47fioqadeabie4m

Astronomical Pipeline Provenance: A Use Case Evaluation [article]

Michael A. C. Johnson, Marcus Paradies, Marta Dembska, Kristen Lackeos, Hans-Rainer Klöckner, David J. Champion, Sirko Schindler
2021 arXiv   pre-print
This analysis is subsequently used as the basis to discuss the requirements, challenges, and opportunities involved in designing both the tool and the associated provenance model.  ...  The intention of this paper is to lay the foundation for making an automated provenance generation tool for astronomical/data-processing pipelines.  ...  A large-scale analysis of already run pipelines may result in a taxonomy of components and pipelines.  ... 
arXiv:2109.10759v1 fatcat:pqjvpi5pubhn7abhcubwaxdjbe

Cross-scale Integrated Biomaging by 3D Light-, X-ray and Electron Microscopy - From Organisms, Organs and Tissue to Cells, Organelles and Macromolecular Complexes

Manfred Auer
2017 Microscopy and Microanalysis  
The entire range of scales spans at least six orders of magnitude, ranging from sub-nanometer to millimeters, and thus cannot be imaged by a single imaging modality alone.  ...  Xray tomography at different scales and resolution.  ...  The entire range of scales spans at least six orders of magnitude, ranging from sub-nanometer to millimeters, and thus cannot be imaged by a single imaging modality alone.  ... 
doi:10.1017/s1431927617002379 fatcat:7qzd6hxtpjc45jescgg75ypbtm

Providing traceability for neuroimaging analyses

Richard McClatchey, Andrew Branson, Ashiq Anjum, Peter Bloodsworth, Irfan Habib, Kamran Munir, Jetendr Shamdasani, Kamran Soomro
2013 International Journal of Medical Informatics  
For neuroscientific analyses, especially those centred on complex image analysis, traceability of processes and datasets is essential but up to now this has not been captured in a manner that facilitates  ...  Over the past decade, we have been working with mammographers, paediatricians and neuroscientists in three generations of projects to provide the data management and provenance services now required for  ...  CRISTAL [19] is essentially a provenance tracking system which has previously been used to track the construction of large-scale experiments e.g. the CMS project [20] at CERN.  ... 
doi:10.1016/j.ijmedinf.2013.05.005 pmid:23763909 fatcat:c3yyjdxqizgp7hlowa32zfthny

Statistical Methods for Image Segmentation and Tomography Reconstruction

M Comer, C Bouman, J Simmons
2010 Microscopy and Microanalysis  
science and medical image analysis.  ...  Our multiscale method works by first reconstructing a coarse resolution reconstruction, then progressing from the coarse scale to finer scales, and finally obtaining a reconstruction at the highest resolution  ...  science and medical image analysis.  ... 
doi:10.1017/s1431927610057442 fatcat:5ecjybgwcze5vipllcb7nbxn6u

Computed tomography texture-based radiomics analysis in gallbladder cancer: initial experience

Pankaj Gupta, Pratyaksha Rana, Balaji Ganeshan, Daneshwari Kalage, Santosh Irrinki, Vikas Gupta, Thakur Deen Yadav, Rajender Kumar, Chandan K. Das, Parikshaa Gupta, Raymond Endozo, Ritambhra Nada (+4 others)
2021 Clinical and Experimental Hepatology  
The only texture parameter that was significantly associated with survival was kurtosis (p = 0.020) at medium texture scales.  ...  There were significant differences in mean and kurtosis at medium texture scales to differentiate moderately differentiated and poorly differentiated adenocarcinoma (p < 0.05).  ...  Contrast enhanced axial CT image of a female patient with pathologically proven gallbladder cancer with texture features.  ... 
doi:10.5114/ceh.2021.111173 pmid:35402717 pmcid:PMC8977886 fatcat:ugegpzboyrbwvek4he4imh2gai
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