XSEDE-enabled high-throughput lesion activity assessment

Hui Zhang, Guangchen Ruan, Hongwei Shen, Michael J. Boyles, Huian Li, Masatoshi Ando

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Caries lesion activity assessment has been a routine diagnostic procedure in dental caries management, traditionally employing subjective measurements incorporating visual and tactile inspections. Recently, advances in 2D/3D image processing and analysis methods and microfocus x-ray computerized tomography (m-CT) hard- ware, together with increased power of high performance computing, have created a synergic effect that is revolutionizing many fields in dental computing. In this paper, we report such an XSEDE- enabled high-throughput lesion activity assessment workflow that exploits 2D/3D image processing, visual analytics, and high performance computing technologies. Our paper starts with a brief introduction of the image dataset in our dental studies. We then proceed to a family of 2D image analysis, ROI segmentation, and 3D geometric construction methods. By combining dental imaging technology and 2D/3D image processing algorithms, we trans- form the task of lesion activity assessment into a 3D-time series analysis of computer generated lesion models. Building on the computational algorithms and implementation models, we develop a high-throughput dental computing workflow exploiting MapReduce tasks to parallelize the image analysis of dental CT scans, the segmentation of region-of-interest (ROI), and the 3D construction of lesion volumes. We showcase the employment of 3D-time series analysis and several other information representations that are applied to our lesion activity assessment scenario focusing on large scale dental image data.

Original languageEnglish (US)
Title of host publicationACM International Conference Proceeding Series
DOIs
StatePublished - 2013
EventConference on Extreme Science and Engineering Discovery Environment, XSEDE 2013 - San Diego, CA, United States
Duration: Jul 22 2013Jul 25 2013

Other

OtherConference on Extreme Science and Engineering Discovery Environment, XSEDE 2013
CountryUnited States
CitySan Diego, CA
Period7/22/137/25/13

Fingerprint

Image analysis
Image processing
Time series analysis
Computerized tomography
Throughput
Computer hardware
Inspection
Imaging techniques
X rays

Keywords

  • Caries lesion activity
  • Dental computing
  • Mapreduce
  • XSEDE

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Software

Cite this

Zhang, H., Ruan, G., Shen, H., Boyles, M. J., Li, H., & Ando, M. (2013). XSEDE-enabled high-throughput lesion activity assessment. In ACM International Conference Proceeding Series [10] https://doi.org/10.1145/2484762.2484783

XSEDE-enabled high-throughput lesion activity assessment. / Zhang, Hui; Ruan, Guangchen; Shen, Hongwei; Boyles, Michael J.; Li, Huian; Ando, Masatoshi.

ACM International Conference Proceeding Series. 2013. 10.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhang, H, Ruan, G, Shen, H, Boyles, MJ, Li, H & Ando, M 2013, XSEDE-enabled high-throughput lesion activity assessment. in ACM International Conference Proceeding Series., 10, Conference on Extreme Science and Engineering Discovery Environment, XSEDE 2013, San Diego, CA, United States, 7/22/13. https://doi.org/10.1145/2484762.2484783
Zhang H, Ruan G, Shen H, Boyles MJ, Li H, Ando M. XSEDE-enabled high-throughput lesion activity assessment. In ACM International Conference Proceeding Series. 2013. 10 https://doi.org/10.1145/2484762.2484783
Zhang, Hui ; Ruan, Guangchen ; Shen, Hongwei ; Boyles, Michael J. ; Li, Huian ; Ando, Masatoshi. / XSEDE-enabled high-throughput lesion activity assessment. ACM International Conference Proceeding Series. 2013.
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