A hybrid human-computer approach for large-scale image-based measurements using web services and machine learning

Author

Maree, Raphael ; Rollus, Loic ; Stevens, Benjamin ; Louppe, Gilles ; Caubo, Olivier ; Rocks, Natacha ; Bekaert, Sandrine ; Cataldo, Didier ; Wehenkel, Louis

Author_Institution

GIGA Bioinf. Core Facility, Univ. of Liege, Liege, Belgium

fYear

2014

fDate

April 29 2014-May 2 2014

Firstpage

902

Lastpage

906

Abstract

We present a novel methodology combining Web-based software development practices, machine learning, and spatial databases for computer-aided quantification of regions of interest (ROIs) in large-scale imaging data. We describe our main methodological choices, and then illustrate the benefits of the approach (workload reduction, improved precision, scalability, and traceability) on hundreds of whole-slide images of biological tissue slices in cancer research.

Keywords

Web services; biomedical optical imaging; cancer; learning (artificial intelligence); medical image processing; tumours; visual databases; Web services; biological tissue slices; cancer research; computer-aided quantification; hybrid human-computer approach; large-scale image-based measurements; large-scale imaging data; machine learning; precision; regions-of-interest; scalability; spatial databases; traceability; whole-slide images; workload reduction; Imaging; Informatics; Lungs; Manuals; Spatial databases; Tumors; hybrid human-computer; imaging informatics; machine learning; rich internet application;

fLanguage

English

Publisher

ieee

Conference_Titel

Biomedical Imaging (ISBI), 2014 IEEE 11th International Symposium on

Conference_Location

Beijing

Type

conf

DOI

10.1109/ISBI.2014.6868017

Filename

6868017