A visual latent semantic approach for automatic analysis and interpretation of anaplastic medulloblastoma virtual slides

Angel Cruz-Roa, Fabio González, Joseph Galaro, Alexander R. Judkins, David Ellison, Jennifer Baccon, Anant Madabhushi, Eduardo Romero

Research output: Chapter in Book/Report/Conference proceedingConference contribution

18 Citations (Scopus)

Abstract

A method for automatic analysis and interpretation of histopathology images is presented. The method uses a representation of the image data set based on bag of features histograms built from visual dictionary of Haar-based patches and a novel visual latent semantic strategy for characterizing the visual content of a set of images. One important contribution of the method is the provision of an interpretability layer, which is able to explain a particular classification by visually mapping the most important visual patterns associated with such classification. The method was evaluated on a challenging problem involving automated discrimination of medulloblastoma tumors based on image derived attributes from whole slide images as anaplastic or non-anaplastic. The data set comprised 10 labeled histopathological patient studies, 5 for anaplastic and 5 for non-anaplastic, where 750 square images cropped randomly from cancerous region from whole slide per study. The experimental results show that the new method is competitive in terms of classification accuracy achieving 0.87 in average.

Original languageEnglish (US)
Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI2012 - 15th International Conference, Proceedings
EditorsNicholas Ayache, Herve Delingette, Polina Golland, Kensaku Mori
PublisherSpringer Verlag
Pages157-164
Number of pages8
ISBN (Print)9783642334146
StatePublished - Jan 1 2012
Event15th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2012 - Nice, France
Duration: Oct 1 2012Oct 5 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7510 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other15th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2012
CountryFrance
CityNice
Period10/1/1210/5/12

Fingerprint

Semantics
Glossaries
Tumors
Interpretability
Histogram
Discrimination
Patch
Interpretation
Vision
Tumor
Attribute
Experimental Results

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Cruz-Roa, A., González, F., Galaro, J., Judkins, A. R., Ellison, D., Baccon, J., ... Romero, E. (2012). A visual latent semantic approach for automatic analysis and interpretation of anaplastic medulloblastoma virtual slides. In N. Ayache, H. Delingette, P. Golland, & K. Mori (Eds.), Medical Image Computing and Computer-Assisted Intervention, MICCAI2012 - 15th International Conference, Proceedings (pp. 157-164). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7510 LNCS). Springer Verlag.
Cruz-Roa, Angel ; González, Fabio ; Galaro, Joseph ; Judkins, Alexander R. ; Ellison, David ; Baccon, Jennifer ; Madabhushi, Anant ; Romero, Eduardo. / A visual latent semantic approach for automatic analysis and interpretation of anaplastic medulloblastoma virtual slides. Medical Image Computing and Computer-Assisted Intervention, MICCAI2012 - 15th International Conference, Proceedings. editor / Nicholas Ayache ; Herve Delingette ; Polina Golland ; Kensaku Mori. Springer Verlag, 2012. pp. 157-164 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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abstract = "A method for automatic analysis and interpretation of histopathology images is presented. The method uses a representation of the image data set based on bag of features histograms built from visual dictionary of Haar-based patches and a novel visual latent semantic strategy for characterizing the visual content of a set of images. One important contribution of the method is the provision of an interpretability layer, which is able to explain a particular classification by visually mapping the most important visual patterns associated with such classification. The method was evaluated on a challenging problem involving automated discrimination of medulloblastoma tumors based on image derived attributes from whole slide images as anaplastic or non-anaplastic. The data set comprised 10 labeled histopathological patient studies, 5 for anaplastic and 5 for non-anaplastic, where 750 square images cropped randomly from cancerous region from whole slide per study. The experimental results show that the new method is competitive in terms of classification accuracy achieving 0.87 in average.",
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Cruz-Roa, A, González, F, Galaro, J, Judkins, AR, Ellison, D, Baccon, J, Madabhushi, A & Romero, E 2012, A visual latent semantic approach for automatic analysis and interpretation of anaplastic medulloblastoma virtual slides. in N Ayache, H Delingette, P Golland & K Mori (eds), Medical Image Computing and Computer-Assisted Intervention, MICCAI2012 - 15th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7510 LNCS, Springer Verlag, pp. 157-164, 15th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2012, Nice, France, 10/1/12.

A visual latent semantic approach for automatic analysis and interpretation of anaplastic medulloblastoma virtual slides. / Cruz-Roa, Angel; González, Fabio; Galaro, Joseph; Judkins, Alexander R.; Ellison, David; Baccon, Jennifer; Madabhushi, Anant; Romero, Eduardo.

Medical Image Computing and Computer-Assisted Intervention, MICCAI2012 - 15th International Conference, Proceedings. ed. / Nicholas Ayache; Herve Delingette; Polina Golland; Kensaku Mori. Springer Verlag, 2012. p. 157-164 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7510 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Cruz-Roa A, González F, Galaro J, Judkins AR, Ellison D, Baccon J et al. A visual latent semantic approach for automatic analysis and interpretation of anaplastic medulloblastoma virtual slides. In Ayache N, Delingette H, Golland P, Mori K, editors, Medical Image Computing and Computer-Assisted Intervention, MICCAI2012 - 15th International Conference, Proceedings. Springer Verlag. 2012. p. 157-164. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).