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Real-time spatial registration for 3D human atlas

  • Lu Chen
  • , Dejun Teng
  • , Tian Zhu
  • , Jun Kong
  • , Bruce W. Herr
  • , Andreas Bueckle
  • , Katy Börner
  • , Fusheng Wang
  • Stony Brook University
  • Shandong University
  • Georgia State University
  • Indiana University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

The human body is made up of about 37 trillion cells (adults). Each cell has its own unique role and is affected by its neighboring cells and environment. The NIH Human BioMolecular Atlas Program (HuBMAP) aims at developing a 3D atlas of human body consisting of organs, vessels, tissues to singe cells with all 3D spatially registered in a single 3D human atlas using tissues obtained from normal individuals across a wide range of ages. A critical step of building the atlas is to register 3D tissue blocks in real-time to the right location of a human organ, which itself consists of complex 3D sub-structures. The complexity of the 3D organ model, e.g., 35 meshes for a typical kidney, poses a significant computational challenge for the registration. In this paper, we propose a comprehensive framework TICKET (TIssue bloCK rEgisTration) to support tissue block registration for 3D human atlas, including (1) 3D mesh pre-processing, (2) spatial queries on intersection relationship and (3) intersection volume computation between organs and tissue blocks. To minimize search space and computation cost, we develop multi-level indexing at both the anatomical structure level and mesh level, and utilize OpenMP for parallel computing. Considering cuboid based shape of the tissue block, we propose an efficient voxelization-based method to estimate the intersection volume. Our experiments demonstrate that the proposed framework is efficient and practical. TICKET is being integrated into the HuBMAP CCF registration portal [1].

Original languageEnglish
Title of host publicationProceedings of the 10th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, BigSpatial 2022
EditorsAshwin Shashidharan, Krishna Karthik Gadiraju, Varun Chandola, Ranga Raju Vatsavai
PublisherAssociation for Computing Machinery, Inc
Pages27-35
Number of pages9
ISBN (Electronic)9781450395311
DOIs
StatePublished - Nov 1 2022
Event10th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, BigSpatial 2022 - Seattle, United States
Duration: Nov 1 2022 → …

Publication series

NameProceedings of the 10th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, BigSpatial 2022

Conference

Conference10th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data, BigSpatial 2022
Country/TerritoryUnited States
CitySeattle
Period11/1/22 → …

Keywords

  • 3D spatial queries
  • human atlas
  • parallel computing
  • spatial indexing

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