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Boosting accuracy of automated classification of fluorescence microscope images for location proteomics
2004
BMC Bioinformatics
Preserved Fulltext
The availability of accurate, fast, automated classification systems for protein location patterns in conjunction with high throughput fluorescence microscope imaging techniques enables a new subfield ...
of proteomics, location proteomics. ...
Acknowledgments We thank William Dirks and Adrienne Wells for programming and preliminary work on applying wavelet features to protein location patterns, and Dr. ...
doi:10.1186/1471-2105-5-78
pmid:15207009
pmcid:PMC449699
fatcat:jcedg5tzcfbudojmzwcxvozmru
Automated analysis of Human Protein Atlas immunofluorescence images
2009
2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro
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The Human Protein Atlas is a rich source of location proteomics data. In this work, we present an automated approach for processing and classifying major subcellular patterns in the Atlas images. ...
degree of accuracy, up to 87.5% for all of the samples and 98.5% when only considering samples in whose classification assignments we are most confident. ...
INTRODUCTION The Human Protein Atlas is a rich source of location proteomic data [1] . ...
doi:10.1109/isbi.2009.5193229
pmid:20628548
pmcid:PMC2901900
dblp:conf/isbi/NewbergLRPULM09
fatcat:vtpuj6jzxrdxll36ilh3agxbja
From quantitative microscopy to automated image understanding
2004
Journal of Biomedical Optics
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Although many of the latest digital signal processing techniques have been successfully applied to compress, restore, and register digital microscope images, automated approaches for recognition and understanding ...
We describe a systematic approach for interpreting protein subcellular distributions using various sets of subcellular location features (SLF), in combination with supervised classification and unsupervised ...
We coined the term location proteomics to describe the combination of tag-ging, imaging, and automated image interpretation to enable a proteome-wide study of subcellular location. 5 The necessity of ...
doi:10.1117/1.1779233
pmid:15447010
pmcid:PMC1458526
fatcat:b3fzgpl2lzh2hepqd76lrh66vy
Automated Blood Cell Detection and Counting via Deep Learning for Microfluidic Point-of-Care Medical Devices
[article]
2019
arXiv
pre-print
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Our experimental results demonstrated that fast and efficient analysis of blood cells via automated microscopic imaging can achieve much better accuracy and faster speed than the conventionally applied ...
However, it is a great challenge to obtain and then predict the precise information of live cells from numerous microscopic videos and images. ...
However, lacking of automation and intelligent procedures has become a critical barrier for the integration of microscopic image analysis into microfluidic POC diagnostic system [3, 4] . ...
arXiv:1909.05393v1
fatcat:y6u2yw7yhvh2vio3pulv5zcxry
Automated Blood Cell Detection and Counting via Deep Learning for Microfluidic Point-of-Care Medical Devices
2019
IOP Conference Series: Materials Science and Engineering
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Our experimental results demonstrated that fast and efficient analysis of blood cells via automated microscopic imaging can achieve much better accuracy and faster speed than the conventionally applied ...
However, it is a great challenge to obtain and then predict the precise information of live cells from numerous microscopic videos and images. ...
However, lacking of automation and intelligent procedures has become a critical barrier for the integration of microscopic image analysis into microfluidic POC diagnostic system [3, 4] . ...
doi:10.1088/1757-899x/646/1/012048
fatcat:5diyobsubfaldivhyfiysrwrwa
Bird Eye View of Protein Subcellular Localization Prediction
2020
Life
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In addition, it is essential for proteins to be destined to their specific locations or compartments to perform their structure and functions. ...
We hope the review will be useful for the researchers working in the field of protein localization predictions. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/life10120347
pmid:33327400
pmcid:PMC7764902
fatcat:4kfiezcrlfh4vmjh6bh5ysgwty
Evaluation of FRET X for Single-Molecule Protein Fingerprinting
[article]
2021
biorxiv/medrxiv
pre-print
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We anticipate that our FRET X fingerprinting approach will form the basis of an analysis tool for targeted proteomics. ...
In a simulated complex mixture of >300 human proteins of which only cysteines, lysines and arginines were labeled, a support vector machine was able to identify constituents with 95% accuracy. ...
For automated detection of individual fluorescence imager strand binding events, we used a custom Python code (Python 3.7, Python Software Foundation, https:// www.python.org) utilizing a two-state K-means ...
doi:10.1101/2021.06.30.450512
fatcat:gwo6ys33djglpomfybaauxfuoi
Modern Trends in Imaging X: Spectral Imaging in Preclinical Research and Clinical Pathology
2012
Analytical Cellular Pathology
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This chapter will present an overview of the rationale for spectral imaging, and discuss the hardware, software and sample labeling strategies that can optimize its usefulness in clinical settings. ...
These tools can provide valuable insights into the basic mechanisms of life, and yield diagnostic and prognostic information for clinical applications. ...
Why use microscope-based imaging for molecular phenotyping? ...
doi:10.1155/2012/904828
pmid:22475632
pmcid:PMC4605801
fatcat:5ktr6lizlje6voujowl4hummqu
Automatic breast cancer cell classification using deep convolutional neural networks
2020
Journal of Science Humanities and Arts - JOSHA
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Automated cell classification in cancer biology is an active and challenging task for computer vision and machine learning algorithms. ...
We then train a Convolutional Neural Network architecture to perform classification using per-cell labels obtained from fluorescence microscopy images associated with each brightfield image. ...
Abstract Automated cell classification in cancer biology is an active and challenging task for computer vision and machine learning algorithms. ...
doi:10.17160/josha.7.2.652
fatcat:xlfua5eoqrckzobw2dbxgzlazm
Happenings in histopathology - a post-World War II perspective
2007
Annals of the Academy of Medicine, Singapore
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biopsy tissues) and globalisation (international associations, standardised classification and nomenclature, and telepathology). ...
Advances in the fields of molecular pathology and telepathology are expected to have the greatest impact on the practice of pathology in the next decade. ...
In the dynamic system, pathologists view images in real time by exerting robotic control over remotely located microscopes. ...
pmid:17767342
fatcat:37m7m7w4yna73hyfin26n7r6xe
Computational pathology: Challenges and promises for tissue analysis
2011
Computerized Medical Imaging and Graphics
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Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:
2015 pre-print arXiv:1601.00027v1 fatcat:m3ebaud3ybgdpcnimh2pxge6fm
Methods for classification, grouping and segmentation of heterogeneous data sources as well as regression of noisy dependencies and estimation of survival probabilities enter the processing workflow of ...
The histological assessment of human tissue has emerged as the key challenge for detection and treatment of cancer. ...
Norbert Wey for scanning and tiling the TMA slides. ...
doi:10.1016/j.compmedimag.2011.02.006
pmid:21481567
fatcat:tqt3tifx5nfihlqskchg5afv7y
Cell image classification: a comparative overview
[article]
2022
arXiv
pre-print
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We review three different approaches for cell image classification: numerical feature extraction, end to end classification with neural networks, and transport-based morphometry. ...
of cancer from images acquired using cytological and histological techniques. ...
Acknowledgements This work was supported in part by National Institutes of Health awards GM130825 and GM090033. ...
arXiv:1906.03316v2
fatcat:45icigrv5zhgxa3afs62hyjrki
Revealing architectural order with polarized light imaging and deep neural networks
[article]
2019
bioRxiv
pre-print
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Our open-source python software for reconstruction of optical properties and training the neural networks is available on GitHub. ...
However, identification of specific structures seen in these images has remained challenging. ...
We also thank Eva Dyer from Georgia Tech for discussions about applications of the 2.5D models. This research was supported by the Chan Zuckerberg Biohub.
Bibliography ...
doi:10.1101/631101
fatcat:grjmxtbj4bewzjkpakh6zh4jsu
A State-of-the-art Survey for Microorganism Image Segmentation Methods and Future Potential
2019
IEEE Access
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A clear explanation of the suitability of these methods for different segmentation challenges encountered on microscopic microorganism images is also enlightened. ...
INDEX TERMS Microorganism segmentation, content-based microscopic image analysis, feature extraction, microscopic images, classical methods, machine learning. ...
Patrice Monkam for his proof reading work and Miss Zixian Li for her important discussion. ...
doi:10.1109/access.2019.2930111
fatcat:3xuu5nj7xnfdhpt6nsvrrlbe5u
AVENUES TO EARLY DETECTION OF ORAL PREMALIGNANT AND MALIGNANT LESIONS: A REVIEW OF THE CURRENT TECHNOLOGIES
English
2014
Journal of Evolution of Medical and Dental Sciences
English
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, Spectral Cytopathology, A multispectral digital microscope (MDM), Optical coherence tomography, Oral Auto fluorescence. ...
In spite of the advances in the therapy for management of Oral Cancer the prognosis still remains poor. ...
Advances in the field of molecular biology, salivary genomics and proteomics have led to the discovery of new molecular markers for oral cancer diagnosis, therapeutics and prognosis. ...
doi:10.14260/jemds/2014/3750
fatcat:zqexzwz5zffbbaso5mxf2jeufy
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