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Medical Image Dataset Processing over Cloud/MapReduce with Heterogeneous Architectures

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Encyclopedia of GIS

Synonyms

Cloud; CPU-GPU; Digital pathology; MapReduce; Pathology imaging; Spatial queries

Footnote 1

Definition

Digital pathology images or whole slide images (Cooper et al. 2012b) are generated through scanning human tissue specimens with high-resolution microscope scanners. Examination of high-resolution whole slide images enables more effective diagnosis, prognosis, and prediction of cancer and other complex diseases (Cooper et al. 2011; Kong et al. 2013).

Pathology image analysis (Cooper et al. 2011; Kong et al. 2011) segments large number of spatial objects, such as nuclei and blood vessels, from whole slide images, along with many image features from these objects. Extracted spatial objects are represented with their geometric boundaries, and such spatially derived information is used in many analytical queries to support biomedical research (Cooper et al. 2012a; Kong et al. 2013) and exploration.

Cloud Computing refers to both the applications delivered as services over the...

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Notes

  1. 1.

    Content is based on the work performed at Emory University as a Ph.D. student.

References

  • Abouzeid A, Bajda-Pawlikowski K, Abadi D, Silberschatz A, Rasin A (2009) HadoopDB: an architectural hybrid of MapReduce and DBMS technologies for analytical workloads. Proc VLDB Endow 2(1):922–933

    Article  Google Scholar 

  • Aji A, Wang F, Saltz JH (2012) Towards building a high performance spatial query system for large scale medical imaging data. In: SIGSPATIAL/GIS, Redondo Beach, pp 309–318. ACM

    Google Scholar 

  • Aji A, Wang F, Vo H, Lee R, Liu Q, Zhang X, Saltz J (2013) Hadoop-GIS: a high performance spatial data warehousing system over MapReduce. Proc VLDB Endow 6(11):1009–1020

    Article  Google Scholar 

  • Aji A, George T, Wang F (2014) Haggis: turbocharge a MapReduce based spatial data warehousing system with GPU engine. In: ACM SIGSPATIAL international workshop on analytics for big geospatial data (BigSpatial’14), Redondo Beach

    Google Scholar 

  • Audet S, Albertsson C, Murase M, Asahara A (2013) Robust and efficient polygon overlay on parallel stream processors. In: Proceedings of the 21st ACM SIGSPATIAL international conference on advances in geographic information systems (SIGSPATIAL’13). ACM, New York, pp 304–313

    Google Scholar 

  • Brinkhoff T, Kriegel H-P, Seeger B (1996) Parallel processing of spatial joins using R-trees. In: ICDE, Redondo Beach

    Book  Google Scholar 

  • Cooper L, Kong J, Moreno C, Wang F, Kurc T, Saltz J, Brat D (2011) In silico analysis of nuclei in glioblastoma using large-scale microscopy images improves prediction of treatment response. In: EMBC, Redondo Beach

    Google Scholar 

  • Cooper LAD, Kong J, Gutman DA, Wang F, Gao J, Appin C, Cholleti S, Pan T, Sharma A, Scarpace L, Mikkelsen T, Kurc T, Moreno CS, Brat DJ, Saltz JH (2012a) Integrated morphologic analysis for the identification and characterization of disease subtypes. J Am Med Inform Assoc 19(2):317–323

    Article  Google Scholar 

  • Cooper LAD, Carter AB, Farris AB, Wang F, Kong J, Gutman DA, Widener P, Pan TC, Cholleti SR, Sharma A et al (2012b) Digital pathology: data-intensive frontier in medical imaging. Proc IEEE 100(4):991–1003

    Article Google Scholar 

  • Dean J, Ghemawat S (2008) Mapreduce: simplified data processing on large clusters. Commun ACM 51(1):107–113

    Article  Google Scholar 

  • Goodchild MF (2007) Citizens as sensors: the world of volunteered geography. GeoJournal 69(4):211–221

    Article  Google Scholar 

  • Kong J, Cooper L, Wang F, Chisolm C, Moreno C, Kurc T, Widener P, Brat D, Saltz J (2011) A comprehensive framework for classification of nuclei in digital microscopy imaging: an application to diffuse gliomas. In: ISBI, Redondo Beach

    Google Scholar 

  • Kong J, Cooper LAD, Wang F, Gao J, Teodoro G, Scarpace L, Mikkelsen T, Schniederjan MJ, Moreno CS, Saltz JH et al (2013) Machine-based morphologic analysis of glioblastoma using whole-slide pathology images uncovers clinically relevant molecular correlates. PLoS One 8(11):e81049

    Article  Google Scholar 

  • Lo M-L, Ravishankar CV (1996) Spatial hash-joins. In: SIGMOD, Redondo Beach, pp 247–258

    Google Scholar 

  • Patel J et al (1997) Building a scaleable geo-spatial dbms: technology, implementation, and evaluation. In: SIGMOD, Redondo Beach, pp 336–347

    Google Scholar 

  • Pavlo A, Paulson E, Rasin A, Abadi DJ, DeWitt DJ, Madden S, Stonebraker M (2009) A comparison of approaches to large-scale data analysis. In: SIGMOD, Redondo Beach, pp 165–178

    Google Scholar 

  • Purcell TJ, Buck I, Mark WR, Hanrahan P (2002) Ray tracing on programmable graphics hardware. ACM Trans Graph (TOG) 21:703–712. ACM

    Google Scholar 

  • Puri S, Prasad SK (2014) GIS polygon overlay processing: new parallel algorithm and system prototype

    Google Scholar 

  • Puri S, Prasad S (2015) A parallel algorithm for clipping polygons with improved bounds and a distributed overlay processing system using mpi. In: 15th IEEE/ACM international symposium on cluster, cloud and grid computing (CCGrid), Redondo Beach. http://cs.gsu.edu/~spuri2/publications/ParallelGH_PI-GIS.pdf

  • Ray S, Simion B, Brown AD, Johnson R (2013) A parallel spatial data analysis infrastructure for the cloud. In: Proceedings of the 21st ACM SIGSPATIAL international conference on advances in geographic information systems (SIGSPATIAL’13). ACM, New York, pp 284–293

    Google Scholar 

  • Sadilek A, Kautz H (2013) Modeling the impact of lifestyle on health at scale. In: Proceedings of the sixth ACM international conference on Web search and data mining, Redondo Beach. ACM, pp 637–646

    Google Scholar 

  • Teodoro G, Kurc TM, Pan T, Cooper LAD, Kong J, Widener P, Saltz JH (2012) Accelerating large scale image analyzes on parallel, CPU-GPU equipped systems. In: 26th IEEE international parallel and distributed processing symposium (IPDPS), Redondo Beach, pp 1093–1104

    Google Scholar 

  • Teodoro G, Pan T, Kurc T, Kong J, Cooper L, Saltz J (2013a) Efficient irregular wavefront propagation algorithms on hybrid CPU-GPU machines. Parallel Comput 39(4):189–211

    Article  Google Scholar 

  • Teodoro G, Pan T, Kurc TM, Kong J, Cooper LAD, Podhorszki N, Klasky S, Saltz JH (2013b) High-throughput analysis of large microscopy image datasets on CPU-GPU cluster platforms. In: proceedings of the 2013 IEEE international symposium on parallel and distributed Processing (IPDPS’13), Redondo Beach

    Google Scholar

  • Teodoro G, Kurc T, Kong J, Cooper L, Saltz J (2014a) Comparative performance analysis of Intel (R) Xeon Phi (TM), GPU, and CPU: a case study from microscopy image analysis. In: 2014 IEEE 28th international parallel and distributed processing symposium (IPDPS ’14), Redondo Beach, pp 1063–1072

    Google Scholar 

  • Teodoro G, Pan T, Kurc T, Kong J, Cooper L, Klasky S, Saltz J (2014b) Region templates: data representation and management for high-throughput image analysis. Parallel Comput 40(10):589–610

    Article  Google Scholar 

  • Vo H, Aji A, Wang F (2014) SATO: a spatial data partitioning framework for scalable query processing. In: SIGSPATIAL/GIS, Redondo Beach. ACM

    Book  Google Scholar 

  • Wang F, Kong J, Cooper L, Pan T, Tahsin K, Chen W, Sharma A, Niedermayr C, Oh TW, Brat D, Farris AB, Foran D, Saltz J (2011) A data model and database for high-resolution pathology analytical image informatics. J Pathol Inform 2(1):32

    Article  Google Scholar 

  • Wang K, Huai Y, Lee R, Wang F, Zhang X, Saltz JH (2012) Accelerating pathology image data cross-comparison on CPU-GPU hybrid systems. Proc VLDB Endow 5(11):1543–1554

    Article  Google Scholar 

  • Wang F, Kong J, Gao J, Adler D, Cooper L, Vergara-Niedermayr C, Zhou Z, Katigbak B, Kurc T, Brat D, Saltz J (2013) A high-performance spatial database based approach for pathology imaging algorithm evaluation. J Pathol Inf 4(5)

    Google Scholar 

  • You S, Zhang J, Gruenwald L (2013) Parallel spatial query processing on GPUs using R-trees. In: Proceedings of the 2nd ACM SIGSPATIAL international workshop on analytics for big geospatial data (BigSpatial’13). ACM, New York, pp 23–31

    Google Scholar 

  • Zhou X, Abel DJ, Truffet D (1998) Data partitioning for parallel spatial join processing. GeoInformatica 2(2):175–204

    Article  Google Scholar 

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Correspondence to Fusheng Wang .

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Wang, F., Aji, A., Teodoro, G. (2017). Medical Image Dataset Processing over Cloud/MapReduce with Heterogeneous Architectures. In: Shekhar, S., Xiong, H., Zhou, X. (eds) Encyclopedia of GIS. Springer, Cham. https://doi.org/10.1007/978-3-319-17885-1_1571

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