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Protocols

WND-CHARM specifications

Information


Unique identifier OMICS_06482
Name WND-CHARM
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS
Programming languages C++
Computer skills Advanced
Stability Stable
Maintained Yes

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No version available

Documentation


Publication for WND-CHARM

WND-CHARM citations

 (8)
library_books

A deep learning classifier identifies patients with clinical heart failure using whole slide images of HandE tissue

2018
PLoS One
PMCID: 5882098
PMID: 29614076
DOI: 10.1371/journal.pone.0192726

[…] A GTX 1080-Ti with CUDA 8.0 and cuDNN optimized by AdaGrad [] built into Caffe, with a fixed batch size of 512 where gradients were accumulated over multiple minibatches.The comparative approach used WND-CHARM [] to extract 4059 engineered features from each ROI, including color, pixel statistics, polynomial decompositions, and texture features among others. This rich feature set has shown to perf […]

library_books

Automated discrimination of lower and higher grade gliomas based on histopathological image analysis

2015
J Pathol Inform
PMCID: 4382761
PMID: 25838967
DOI: 10.4103/2153-3539.153914

[…] reviously, there are 51 HGG cases versus 87 LGG cases and the results are given in that is showing significant accuracies in HGG versus LGG classification problem.We also compare our results against WND-CHARM features[] which is known to be a state of the art tool for interpreting and classifying medical images and has been applied successfully in the past to many histopathology classification pr […]

library_books

Automated Diagnosis of Otitis Media: Vocabulary and Grammar

2013
PMCID: 3749602
PMID: 23997759
DOI: 10.1155/2013/327515

[…] f which we designed previously, correlation filter classification system, multiresolution classifier and SIFT and shape description using SVM classifier, and two that are available in the literature, WND-CHARM classifier and random forest classifier. We now briefly describe each of these. Note that for all the experiments, we used a 5-fold cross-validation setup. […]

call_split

Automated classification of immunostaining patterns in breast tissue from the human protein atlas

2013
J Pathol Inform
PMCID: 3678740
PMID: 23766936
DOI: 10.4103/2153-3539.109881
call_split See protocol

[…] “PCA-LDA-CHARM” is an algorithm initially inspired by Ilya Goldberg's WND-CHARM,[] a whole-image-based classifier. The principle of the original algorithm is to extract features on the whole image (without segmenting the interesting parts), weighting the features depend […]

library_books

Phenotype Recognition with Combined Features and Random Subspace Classifier Ensemble

2011
BMC Bioinformatics
PMCID: 3098787
PMID: 21529372
DOI: 10.1186/1471-2105-12-128

[…] .2% for HeLa and 98.9% for CHO), compared to the published results (82% for RNAi, 84% for HeLa and 93% for CHO), which used wavelet as part of the features and a general-purpose classification scheme WND-CHARM. This supports the claim that Random Subspace ensemble can be used as a simple yet efficient classifier design methodolody and curvelet features effectively measure the informativeness in th […]

library_books

Pattern Recognition Software and Techniques for Biological Image Analysis

2010
PLoS Comput Biol
PMCID: 2991255
PMID: 21124870
DOI: 10.1371/journal.pcbi.1000974

[…] to its variance within classes, giving features with high discriminative power higher scores. This approach is implemented in the wndchrm image analysis tool (available at http://ome.grc.nia.nih.gov/wnd-charm/), where the Fisher scores are also used as feature weights. While providing accurate results for a variety of image types , a potential downside of this method is feature redundancy due to […]

Citations

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WND-CHARM institution(s)
Image Informatics and Computational Biology Unit, Laboratory of Genetics, NIA, Baltimore, MD

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