Experiments in Molecular Subtype Recognition Based on
Histopathology Images

D 2016

Experiments in Molecular Subtype Recognition Based on Histopathology Images

BUDINSKÁ, Eva, Fred BOSMAN and Vlad POPOVICI

Basic information

Original name

Experiments in Molecular Subtype Recognition Based on Histopathology Images

Authors

BUDINSKÁ, Eva (703 Slovakia, guarantor, belonging to the institution), Fred BOSMAN (756 Switzerland) and Vlad POPOVICI (642 Romania, belonging to the institution)

Edition

NEW YORK, 2016 IEEE 13TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI), p. 1168-1172, 5 pp. 2016

Publisher

IEEE

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

References:

URL

RIV identification code

RIV/00216224:14310/16:00093777

Organization unit

Faculty of Science

ISBN

978-1-4799-2350-2

ISSN

DOI

http://dx.doi.org/10.1109/ISBI.2016.7493474

UT WoS

000386377400276

Keywords in English

colon cancer; histopathology imaging; classification; gastrointestinal tract

Abstract

V originále

Molecular subtypes have been recently derived for various types of cancer, in an attempt to characterize the inter-tumoral heterogeneity. In this work we explore the possibility of constructing predictors for molecular subtypes based on histopathology images. For this, we introduce a novel 2-level bag-of-features method and we apply it to a collection of colorectal cancer samples. The resulting image features capture some relevant tumor morphology patterns and led to a classifier performing similarly to one constructed from features annotated by an expert pathologist. The significance of our results extends beyond subtype prediction since they demonstrate a possible approach to multimodal (histopathology and molecular) data mining and biomarker identification.

Links

4SGA8736, interní kód MU

Name: Computational framework for joint analysis of histopathology images and gene expression data (Acronym: HIGEX)

Investor: South-Moravian Region, Incoming grants

Citovat

BUDINSKÁ, Eva, Fred BOSMAN and Vlad POPOVICI. Experiments in Molecular Subtype Recognition Based on Histopathology Images. Online. In 2016 IEEE 13TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI). NEW YORK: IEEE, 2016, p. 1168-1172. ISBN 978-1-4799-2350-2. Available from: https://dx.doi.org/10.1109/ISBI.2016.7493474.

@inproceedings{1374296,
   author = {Budinská, Eva and Bosman, Fred and Popovici, Vlad},
   address = {NEW YORK},
   booktitle = {2016 IEEE 13TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI)},
   doi = {http://dx.doi.org/10.1109/ISBI.2016.7493474},
   keywords = {colon cancer; histopathology imaging; classification; gastrointestinal tract},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {NEW YORK},
   isbn = {978-1-4799-2350-2},
   pages = {1168-1172},
   publisher = {IEEE},
   title = {Experiments in Molecular Subtype Recognition Based on Histopathology Images},
   url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7493474},
   year = {2016}
}

TY  - JOUR
ID  - 1374296
AU  - Budinská, Eva - Bosman, Fred - Popovici, Vlad
PY  - 2016
TI  - Experiments in Molecular Subtype Recognition Based on Histopathology Images
PB  - IEEE
CY  - NEW YORK
SN  - 9781479923502
KW  - colon cancer
KW  - histopathology imaging
KW  - classification
KW  - gastrointestinal tract
UR  - http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7493474
L2  - http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7493474
N2  - Molecular subtypes have been recently derived for various types of cancer, in an attempt to characterize the inter-tumoral heterogeneity. In this work we explore the possibility of constructing predictors for molecular subtypes based on histopathology images. For this, we introduce a novel 2-level bag-of-features method and we apply it to a collection of colorectal cancer samples. The resulting image features capture some relevant tumor morphology patterns and led to a classifier performing similarly to one constructed from features annotated by an expert pathologist. The significance of our results extends beyond subtype prediction since they demonstrate a possible approach to multimodal (histopathology and molecular) data mining and biomarker identification.
ER  -

BUDINSKÁ, Eva, Fred BOSMAN and Vlad POPOVICI. Experiments in Molecular Subtype Recognition Based on Histopathology Images. Online. In \textit{2016 IEEE 13TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI)}. NEW YORK: IEEE, 2016, p.~1168-1172. ISBN~978-1-4799-2350-2. Available from: https://dx.doi.org/10.1109/ISBI.2016.7493474.

Detailed Information on Publication Record