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Boosting accuracy of automated classification of fluorescence microscope images for location proteomics

Kai Huang, Robert F Murphy
2004 BMC Bioinformatics  
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

Justin Y. Newberg, Jieyue Li, Arvind Rao, Fredrik Ponten, Mathias Uhlen, Emma Lundberg, Robert F. Murphy
2009 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro  
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

Kai Huang, Robert F. Murphy
2004 Journal of Biomedical Optics  
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]

Tiancheng Xia, Richard Jiang, YongQing Fu, Nanlin Jin
2019 arXiv   pre-print
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

Tiancheng Xia, Richard Jiang, Yong Qing Fu, Nanlin Jin
2019 IOP Conference Series: Materials Science and Engineering  
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

Ravindra Kumar, Sandeep Kumar Dhanda
2020 Life  
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]

Carlos de Lannoy, Mike Filius, Raman van Wee, Chirlmin Joo, Dick de Ridder
2021 biorxiv/medrxiv   pre-print
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

Richard Levenson, Joseph Beechem, George McNamara
2012 Analytical Cellular Pathology  
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

Gisela Pattarone
2020 Journal of Science Humanities and Arts - JOSHA  
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

K Shanmugaratnam
2007 Annals of the Academy of Medicine, Singapore  
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

Thomas J. Fuchs, Joachim M. Buhmann
2011 Computerized Medical Imaging and Graphics  
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]

Mohammad Shifat-E-Rabbi, Xuwang Yin, Cailey Elizabeth Fitzgerald, Gustavo K. Rohde
2022 arXiv   pre-print
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]

Syuan-Ming Guo, Anitha Priya Krishnan, Jenny Folkesson, Ivan Ivanov, Bryant Chhun, Nathan Cho, Manuel Leonetti, Shalin B. Mehta
2019 bioRxiv   pre-print
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

Frank Kulwa, Chen Li, Xin Zhao, Bencheng Cai, Ning Xu, Shouliang Qi, Shuo Chen, Yueyang Teng
2019 IEEE Access  
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

Mohsin Muzaffar Tak, Mohd. Arif Dar
2014 Journal of Evolution of Medical and Dental Sciences  
, 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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