scholarly journals BIAFLOWS: A collaborative framework to reproducibly deploy and benchmark bioimage analysis workflows

2019 ◽  
Author(s):  
Ulysse Rubens ◽  
Romain Mormont ◽  
Lassi Paavolainen ◽  
Volker Bäcker ◽  
Gino Michiels ◽  
...  
Keyword(s):  
Image Analysis ◽  
Software Tool ◽  
Quantitative Information ◽  
Automated Image Analysis ◽  
Complete Case ◽  
Nuclei Segmentation ◽  
Learning Techniques ◽  
Bioimage Analysis ◽  
Reproducible Manner

AbstractAutomated image analysis has become key to extract quantitative information from scientific microscopy bioimages, but the methods involved are now often so refined that they can no longer be unambiguously described using written protocols. We introduce BIAFLOWS, a software tool with web services and a user interface specifically designed to document, interface, reproducibly deploy, and benchmark image analysis workflows. BIAFLOWS allows image analysis workflows to be compared fairly and shared in a reproducible manner, safeguarding research results and promoting the highest quality standards in bioimage analysis. A curated instance of BIAFLOWS is available online; it is currently populated with 34 workflows that can be triggered to process image datasets illustrating 15 common bioimage analysis problems organized in 9 major classes. As a complete case study, the open benchmarking of 7 nuclei segmentation workflows, including classical and deep learning techniques, was performed on this online instance. All the results presented can be reproduced online.

scholarly journals Object-based analysis of UAS imagery to map emergent and submerged invasive aquatic vegetation: a case study

2017 ◽  
Vol 5 (1) ◽  
pp. 27-33 ◽  
Author(s):  
Dominique Chabot ◽  
Christopher Dillon ◽  
Oumer Ahmed ◽  
Adam Shemrock
Keyword(s):  
Image Analysis ◽  
Data Collection ◽  
Near Infrared ◽  
Aquatic Vegetation ◽  
Weather Conditions ◽  
Classification Performance ◽  
Unmanned Aircraft ◽  
Automated Image Analysis ◽  
Object Based

Small unmanned aircraft systems (UAS) combined with automated image analysis may provide an efficient alternative or complement to labour-intensive boat-based monitoring of invasive aquatic vegetation. A small mapping drone was assessed for collecting high-resolution (≤5 cm/pixel) true-colour and near-infrared imagery revealing the distribution of invasive water soldier (Stratiotes aloides) in the Trent–Severn Waterway, Ontario (Canada). We further evaluated the capacity of an object-based image analysis approach based on the Random Forests classification algorithm to map features in the imagery, chiefly emergent and submerged water soldier colonies. The imagery contained flaws and inconsistencies resulting from data collection in suboptimal weather conditions that likely negatively impacted classification performance. Nevertheless, our best-performing classification had a producer’s and user’s accuracy for water soldier of 81% and 74%, respectively, an overall accuracy of 78%, and a kappa value of 61%, indicating “substantial” accuracy. This trial provides an instructive case study on results achieved in a “real-world” application of a UAS for environmental monitoring, notably characterized by time constraints for data collection and analysis. Beyond avoiding data collection in unfavourable weather conditions, adaptations of the image segmentation process and use of a true discrete-band multispectral camera may help to improve classification accuracy, particularly of submerged vegetation.

scholarly journals Automated image analysis of instagram posts: Implications for risk perception and communication in public health using a case study of #HIV

PLoS ONE ◽  
2020 ◽  
Vol 15 (5) ◽  
pp. e0231155 ◽  
Author(s):  
Alicia L. Nobles ◽  
Eric C. Leas ◽  
Seth Noar ◽  
Mark Dredze ◽  
Carl A. Latkin ◽  
...  
Keyword(s):  
Public Health ◽  
Image Analysis ◽  
Risk Perception ◽  
Automated Image Analysis ◽  
Risk Perception And Communication

Automated image analysis of ice thin sections — instrumentation, methods and extraction of stereological and textural parameters

1993 ◽  
Vol 39 (132) ◽  
pp. 341-352 ◽  
Author(s):  
Hajo Eicken
Keyword(s):  
Image Analysis ◽  
Polarized Light ◽  
Ice Crystals ◽  
Automated Image Analysis ◽  
Thin Sections ◽  
Circularly Polarized Light ◽  
Grain Sizes ◽  
Finite Section ◽  
Textural Parameters ◽  
Reproducible Manner

AbstractImage-analysis procedures have been developed for a simple PC-based system to evaluate the textural features of ice thin sections automatically. The method yields parameters that describe both ice crystals and pores in an objective, reproducible manner. Specimens are recorded in linearly and circularly polarized light (ice grains) as well as in transmitted and incident plain light (pores) under standardized conditions. After preparative filtering, images are segmented through union of two Sobel-filtered images (ice crystals/grain boundaries) or through thresholding (ice crystals/pores). The quantification of texture is based on the evaluation of image contrast as well as on linear analysis and non-linear transforms to obtain information on grain-sizes and their distribution. In the study of ice pores, stereological effects of finite section thickness have to be corrected. The discussion focuses on errors involved in automated textural analysis and the glaciological yield of measured and derived parameters.

scholarly journals Image Analysis for Spectroscopic Elemental Dot Maps: P, Al, and Ca Associations in Water Treatment Residuals as a Case Study

2021 ◽  
Vol 2 ◽  
Author(s):  
Iris Zohar ◽  
Peleg Haruzi
Keyword(s):  
Image Analysis ◽  
Water Treatment ◽  
Quantitative Information ◽  
Dairy Wastewater ◽  
Chemical Behavior ◽  
Water Treatment Residuals ◽  
Environmental Implications ◽  
Water Pretreatment ◽  
Working Procedure

The associations of elements upon a heterogeneous surface may control nutrients or pollutants sorption and release, having agricultural and environmental implications. This chemical behavior can be elucidated by spatial spectroscopy, followed by image analysis. The purpose of this paper is to present a working procedure for image analysis using the free program ImageJ that can be applied for dot maps of three or more elements produced by solid-state spectroscopy. Detailed step-by-step instructions lead to visual and quantitative information regarding elements associations. The working procedure was demonstrated for P, Al and Ca dot maps produced by scanning electron microscopy energy dispersive spectroscopy (SEM-EDS) for surfaces of Al-based water treatment residuals (Al-WTRs), a by-product of drinking water pretreatment with alum coagulant. Al-WTR was reused to adsorb the macro-nutrient P from polluted soil leach and dairy wastewater (WW). Surficial P onto Al-WTR, SL-Al/O-WTR, and WW-Al/O-WTR (0.56, 0.93, and 2.15%, respectively) displayed sorption dynamics, mostly with Al and Ca. Quantification of the spatial proportions of individual elements and their associations indicated P-Al pool > P-Ca pool (45–24% and 17–7%, respectively). Upon introducing P-rich dairy wastewater, the behavior of P sorption by Al and Ca changed and became more clustered. A ternary phase of P-Al-Ca covered 38% of the area with signal, compared to 4.3 and 4.6% of the area in Al-WTR and SL-Al-WTR, where it was limited to particles edges only. Thus, the presented protocol may promote employing image analysis for geochemical applications, elucidating chemical behavior and affinities. Advantages and pitfalls are discussed.

scholarly journals Automated image analysis of ice thin sections — instrumentation, methods and extraction of stereological and textural parameters

1993 ◽  
Vol 39 (132) ◽  
pp. 341-352 ◽  
Author(s):  
Hajo Eicken
Keyword(s):  
Image Analysis ◽  
Polarized Light ◽  
Ice Crystals ◽  
Automated Image Analysis ◽  
Thin Sections ◽  
Circularly Polarized Light ◽  
Grain Sizes ◽  
Finite Section ◽  
Textural Parameters ◽  
Reproducible Manner

AbstractImage-analysis procedures have been developed for a simple PC-based system to evaluate the textural features of ice thin sections automatically. The method yields parameters that describe both ice crystals and pores in an objective, reproducible manner. Specimens are recorded in linearly and circularly polarized light (ice grains) as well as in transmitted and incident plain light (pores) under standardized conditions. After preparative filtering, images are segmented through union of two Sobel-filtered images (ice crystals/grain boundaries) or through thresholding (ice crystals/pores). The quantification of texture is based on the evaluation of image contrast as well as on linear analysis and non-linear transforms to obtain information on grain-sizes and their distribution. In the study of ice pores, stereological effects of finite section thickness have to be corrected. The discussion focuses on errors involved in automated textural analysis and the glaciological yield of measured and derived parameters.

scholarly journals An automated image analysis method to measure regularity in biological patterns: a case study in a Drosophila neurodegenerative model

2015 ◽  
Vol 10 (1) ◽  
pp. 9 ◽  
Author(s):  
Sergio Diez-Hermano ◽  
Jorge Valero ◽  
Cristina Rueda ◽  
Maria D Ganfornina ◽  
Diego Sanchez
Keyword(s):  
Image Analysis ◽  
Automated Image Analysis ◽  
Analysis Method ◽  
Image Analysis Method ◽  
Biological Patterns

scholarly journals Workflow and Metrics for Image Quality Control in Large-Scale High-Content Screens

2011 ◽  
Vol 17 (2) ◽  
pp. 266-274 ◽  
Author(s):  
Mark-Anthony Bray ◽  
Adam N. Fraser ◽  
Thomas P. Hasaka ◽  
Anne E. Carpenter
Keyword(s):  
Quality Control ◽  
Image Analysis ◽  
Image Quality ◽  
Data Quality ◽  
Large Scale ◽  
Visual Inspection ◽  
Quantitative Information ◽  
Automated Image Analysis ◽  
High Content Screening ◽  
Image Quality Control

Automated microscopes have enabled the unprecedented collection of images at a rate that precludes visual inspection. Automated image analysis is required to identify interesting samples and extract quantitative information for high-content screening (HCS). However, researchers are impeded by the lack of metrics and software tools to identify image-based aberrations that pollute data, limiting experiment quality. The authors have developed and validated approaches to identify those image acquisition artifacts that prevent optimal extraction of knowledge from high-content microscopy experiments. They have implemented these as a versatile, open-source toolbox of algorithms and metrics readily usable by biologists to improve data quality in a wide variety of biological experiments.

Automated Image Analysis Of Nuclear And Cytoplasmic Changes In Exfoliated Cells From Tracheas Treated With Carcinogen

1977 ◽  
Vol 35 ◽  
pp. 220-221
Author(s):  
S.F. Stinson ◽  
J.C. Lilga ◽  
M.B. Sporn
Keyword(s):  
Image Analysis ◽  
Pattern Analysis ◽  
Relative Proportion ◽  
Automated Image Analysis ◽  
Image Analyzer ◽  
Cross Sectional ◽  
Exfoliated Cells ◽  
Neoplastic Lesions ◽  
Analysis System ◽  
Morphologic Criterion

Increased nuclear size, resulting in an increase in the relative proportion of nuclear to cytoplasmic sizes, is an important morphologic criterion for the evaluation of neoplastic and pre-neoplastic cells. This paper describes investigations into the suitability of automated image analysis for quantitating changes in nuclear and cytoplasmic cross-sectional areas in exfoliated cells from tracheas treated with carcinogen.Neoplastic and pre-neoplastic lesions were induced in the tracheas of Syrian hamsters with the carcinogen N-methyl-N-nitrosourea. Cytology samples were collected intra-tracheally with a specially designed catheter (1) and stained by a modified Papanicolaou technique. Three cytology specimens were selected from animals with normal tracheas, 3 from animals with dysplastic changes, and 3 from animals with epidermoid carcinoma. One hundred randomly selected cells on each slide were analyzed with a Bausch and Lomb Pattern Analysis System automated image analyzer.

Progress In The Practical Application Of Automated Image Analysis To Tem Negatives

1977 ◽  
Vol 35 ◽  
pp. 214-217
Author(s):  
F. A. Heckman ◽  
E. Redman ◽  
J.E. Connolly
Keyword(s):  
Image Analysis ◽  
Image Quality ◽  
Exposure Time ◽  
Image Contrast ◽  
Automated Image Analysis ◽  
Practical Application ◽  
Factors Affecting ◽  
High Image Quality ◽  
Qualitative Evidence ◽  
Comprehensive Study

In our initial publication on this subject1) we reported results demonstrating that contrast is the most important factor in producing the high image quality required for reliable image analysis. We also listed the factors which enhance contrast in order of the experimentally determined magnitude of their effect. The two most powerful factors affecting image contrast attainable with sheet film are beam intensity and KV. At that time we had only qualitative evidence for the ranking of enhancing factors. Later we carried out the densitometric measurements which led to the results outlined below.Meaningful evaluations of the cause-effect relationships among the considerable number of variables in preparing EM negatives depend on doing things in a systematic way, varying only one parameter at a time. Unless otherwise noted, we adhered to the following procedure evolved during our comprehensive study:Philips EM-300; 30μ objective aperature; magnification 7000- 12000X, exposure time 1 second, anti-contamination device operating.

Sign in / Sign up

Export Citation Format

Share Document