Experiments in Molecular Subtype Recognition Based on
Histopathology Images

D 2016

Experiments in Molecular Subtype Recognition Based on Histopathology Images

BUDINSKÁ, Eva, Fred BOSMAN a Vlad POPOVICI

Základní údaje

Originální název

Experiments in Molecular Subtype Recognition Based on Histopathology Images

Autoři

BUDINSKÁ, Eva (703 Slovensko, garant, domácí), Fred BOSMAN (756 Švýcarsko) a Vlad POPOVICI (642 Rumunsko, domácí)

Vydání

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

Nakladatel

IEEE

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

elektronická verze "online"

Odkazy

URL

Kód RIV

RIV/00216224:14310/16:00093777

Organizační jednotka

Přírodovědecká fakulta

ISBN

978-1-4799-2350-2

ISSN

DOI

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

UT WoS

000386377400276

Klíčová slova anglicky

colon cancer; histopathology imaging; classification; gastrointestinal tract

Štítky

AKR, podil, rivok

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 26. 4. 2017 23:13, Ing. Andrea Mikešková

Anotace

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.

Návaznosti

4SGA8736, interní kód MU

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

Investor: Jihomoravský kraj, Computational framework for joint analysis of histopathology images and gene expression data, Granty pro zahraniční vědce

Citovat

BUDINSKÁ, Eva, Fred BOSMAN a 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, s. 1168-1172. ISBN 978-1-4799-2350-2. Dostupné z: 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 a 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, s.~1168-1172. ISBN~978-1-4799-2350-2. Dostupné z: https://dx.doi.org/10.1109/ISBI.2016.7493474.

Podrobný výpis o publikaci