Distributed Medical Image Analysis and Diagnosis through Crowd-Sourced Games: A Malaria Case Study

In this work we investigate whether the innate visual recognition and learning capabilities of untrained humans can be used in conducting reliable microscopic analysis of biomedical samples toward diagnosis. For this purpose, we designed entertaining digital games that are interfaced with artificial learning and processing back-ends to demonstrate that in the case of binary medical diagnostics decisions (e.g., infected vs. uninfected), with the use of crowd-sourced games it is possible to approach the accuracy of medical experts in making such diagnoses. Specifically, using non-expert gamers we report diagnosis of malaria infected red blood cells with an accuracy that is within 1.25% of the diagnostics decisions made by a trained medical professional.

[1]  Zoran Popovic,et al.  PhotoCity: training experts at large-scale image acquisition through a competitive game , 2011, CHI.

[2]  A. Dempster,et al.  Computer vision for microscopy diagnosis of malaria , 2009, Malaria Journal.

[3]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[4]  Derek Tseng,et al.  Lensfree microscopy on a cellphone. , 2010, Lab on a chip.

[5]  Andrew G. Dempster,et al.  Malaria Parasite Detection in Peripheral Blood Images , 2006, BMVC.

[6]  Hongying Zhu,et al.  Cost-effective and compact wide-field fluorescent imaging on a cell-phone. , 2011, Lab on a chip.

[7]  David Baker,et al.  Algorithm discovery by protein folding game players , 2011, Proceedings of the National Academy of Sciences.

[8]  Laura A. Dabbish,et al.  Labeling images with a computer game , 2004, AAAI Spring Symposium: Knowledge Collection from Volunteer Contributors.

[9]  Derek Tseng,et al.  Compact, light-weight and cost-effective microscope based on lensless incoherent holography for telemedicine applications. , 2010, Lab on a chip.

[10]  David Salesin,et al.  The challenge of designing scientific discovery games , 2010, FDG.

[11]  Yun-En Liu,et al.  Gameplay analysis through state projection , 2010, FDG.

[12]  Adrien Treuille,et al.  Predicting protein structures with a multiplayer online game , 2010, Nature.

[13]  Nasser M. Nasrabadi,et al.  Pattern Recognition and Machine Learning , 2006, Technometrics.

[14]  Noah Snavely,et al.  Reconstructing the world in 3D: bringing games with a purpose outdoors , 2010, HCOMP '10.

[15]  Fabio A. González,et al.  A semi-automatic method for quantification and classification of erythrocytes infected with malaria parasites in microscopic images , 2009, J. Biomed. Informatics.

[16]  Athanasios Papoulis,et al.  Probability, Random Variables and Stochastic Processes , 1965 .

[17]  Andrew G. Dempster,et al.  Parasite detection and identification for automated thin blood film malaria diagnosis , 2010, Comput. Vis. Image Underst..

[18]  Y. Kafai.  Playing and Making Games for Learning , 2006, Games Cult..

[19]  Laura A. Dabbish,et al.  Designing games with a purpose , 2008, CACM.

[20]  Claudia Adams,et al.  The use of computer games as an educational tool: identification of appropriate game types and game elements , 1999, Br. J. Educ. Technol..

[21]  A. Ozcan,et al.  Holographic pixel super-resolution in portable lensless on-chip microscopy using a fiber-optic array. , 2011, Lab on a chip.

[22]  David Roman,et al.  Crowdsourcing and the question of expertise , 2009, Commun. ACM.

[23]  S. Ong,et al.  MalariaCount: an image analysis-based program for the accurate determination of parasitemia. , 2007, Journal of microbiological methods.

[24]  David G. Stork,et al.  Pattern Classification , 1973 .

[25]  Bernardo A. Huberman.  Crowdsourcing and Attention , 2008, Computer.

[26]  Manuel Blum,et al.  reCAPTCHA: Human-Based Character Recognition via Web Security Measures , 2008, Science.

[27]  Hongying Zhu,et al.  Optofluidic fluorescent imaging cytometry on a cell phone. , 2011, Analytical chemistry.

[28]  Mark C. Pierce,et al.  Portable, Battery-Operated, Low-Cost, Bright Field and Fluorescence Microscope , 2010, PloS one.

[29]  Amy L. Gryshuk,et al.  Cell-Phone-Based Platform for Biomedical Device Development and Education Applications , 2011, PloS one.

[30]  David N Breslauer,et al.  Mobile Phone Based Clinical Microscopy for Global Health Applications , 2009, PloS one.