MaCrowdsourcingGames

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

Crowdsourcing Games for Medical Applications

Supervision: Shadi Albarqouni

Abstract

Crowdsourcing has been widely used for annotation, i.e. collecting ground-truth, in the medical community. Many studies have shown that non-expert can perform as well as experts in crowdsourcing tasks if they were trained well, however, users/crowd are not motivated to complete the task to the very end. Recently, we showed that games can play a crucial role in motivating the crowd in the annotation task. In this work, we need to extend this to many different use cases.

Tasks:

  • Extend the Playsourcing paper
  • Publish it online for crowdsourcing
  • Compare the results with few baselines

Requirements:

  • Good understanding of statistics and machine learning methods.
  • Very good programming skills in Unity3D, Java, and C++/Python

Location:

  • FMI Building, Garching

Literature

2016
S. Albarqouni, S. Matl, M. Baust, N. Navab, S. Demirci
Playsourcing: A Novel Concept for Knowledge Creation in Biomedical Research
Proceedings of MICCAI Workshop on Large-scale Annotation of Biomedical data and Expert Label Synthesis, Athens, Greece, October 2016
The first two authors contribute equally to this paper.
(bib)
S. Albarqouni, C. Baur, F. Achilles, V. Belagiannis, S. Demirci, N. Navab
AggNet: Deep Learning from Crowds for Mitosis Detection in Breast Cancer Histology Images
IEEE Transactions on Medical Imaging (TMI), Special Issue on Deep Learning, vol. 35, no. 5, pp. 1313 - 1321, 2016.
The first two authors contribute equally to this paper.
(bib)

ProjectForm
Title: Crowdsourcing Games for Medical Applications
Abstract: Crowdsourcing has been widely used for annotation, i.e. collecting ground-truth, in medical community. Many studies have shown that non-expert can perform as well as experts in crowdsourcing tasks if they were trained well, however, users/crowd are not motivated to complete the task to the very end. Recently, we showed that games can play a crucial role in motivating the crowd in the annotation task. In this work, we need to extend this to many different use cases.
Student:  
Director: Prof. Dr. Nassir Navab
Supervisor: Shadi Albarqouni
Type: Bachelor Thesis
Area: Machine Learning, Medical Imaging
Status: draft
Start:  
Finish:  
Thesis (optional):  
Picture:  


Edit | Attach | Refresh | Diffs | More | Revision r1.6 - 05 May 2017 - 08:30 - ShadiAlbarqouni