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HCI Research: Data Segmentation


Ambiguity is present in all types of images.

How do experts resolve ambiguities in interpretation of 3D imaging?

HCI Research: Data Segmentation

Prof. Ruth West (University of North Texas), is engaged in collaborative research with Prof. Cindy Grimm (Oregon State Univserity) and Prof. Tao Ju (Washington University St. Louis) to study the cognitive and perceptual basis of how experts extract 3D shapes from volumetric data, such as electron tomography, MRI or CT imaging. This process, known as “segmentation” plays an essential role in the interpretation and analysis of volume data in a variety of application domains.

Understanding what a segmenter sees, thinks, and does while interacting with a data set will help to make future tools more efficient, alleviating the major scientific bottleneck posed by the time-intensive nature of segmentation. It will also help in developing better tools to improve the accuracy and repeatability of the segmentation process, positively enhancing the quality of the resulting data for use in a variety of  applications, including biomedicine, clinical practice and environmental engineering.

This work is supported by NSF Collaborative: Developing Conceptual Models for Navigation, Marking and Inspection in the Context of 3D Image Segmentation, IIS-1302248, IIS-1302142, IIS-1302200.

IRB Information




  1. Research to understand how we Infer 2D-cross sections from 3D shapes published in Human Factors journal

    Understanding 2D cross-sections of 3D structures is important in medical imaging, biology, geology, art, architecture, physics and engineering. If you’ve ever had an MRI, your radiologist understood 3D spatial information from the 2D image slices that make up that medical imaging.  Identifying and orienting the correct 2D cross-section of a 3D object is a complex set of spatial/visualization skills. In our collaboration with Dr. Anahita Sanadaji (Ohio University), Dr. Cindy Grimm (Oregon...
  2. Collaborative Publication at ACM Applied Perception Symposium

    xREZ Lab collaborated with Oregon State University’s Professor Cindy Grimm and doctoral candidate Anahita Sanandaji on the research published in, “Inferring Cross Sections of 3D Objects: A 3D Spatial Ability Test Instrument for 3D Volume Segmentation” at ACM’s annual Symposium on Applied Perception (SAP), held September 16-17, 2017 in Cottbus, Germany. The paper has been published to the SAP ’17 proceedings. In this article Anahita Sanandaji’s research details development of a modified version of the Santa...
  3. Segmentation Team Publishes at ACM’s Applied Perception Symposium

    The 3D Segmentation team published their fourth paper, “How experts’ mental models affects 3D image segmentation” at ACM’s Symposium on Applied Perception (SAP), held July 22-23, 2016 in Anaheim, California. The ACM published the paper to the SAP ’16  proceedings. The paper outlines the research design behind the following hypothesis: Provided with a 3D structure and slicing plane experts are able to predict the 2D contour, how 2D contour changes with small view changes...
  4. Segmentation Team Publishes at VINCI 2016

    The 3D Segmentation team presented their third paper this year, “Eliciting Tacit Expertise in 3D Volume Segmentation” at the 2016 Symposium on Visual Information Communication and Interaction (VINCI), held Sept.24-26 in Dallas, Texas. The ACM published the paper to the VINCI 2016 symposium proceedings. The paper examines manual (semi-automatic), low-level (perceptual) and high-level decision making by experts dealing with 3D data. The analaysis hopes to provide valuable information used to design more accurate, efficient, easier...
  5. Segmentation Team Publishes at ACM’s ETRA Symposium

    The 3D Segmentation team at xREZ Art + Science Lab published their second paper this year, “Where Do Experts Look While Doing 3D Image Segmentation” at the 2016 Association for Computing Machinery’s (ACM) Symposium on Eye Tracking Research & Applications (ETRA), held March 14-17 in Charleston, South Carolina. The ACM published the paper to the ETRA 2016 symposium proceedings. Anahita Sanandaji of Oregon State University, Ruth West of the University of North...
  6. Segmentation Team Wins Best Paper at ISVC 2015

    xREZ Lab’s 3D Segmentation research team won best paper for their publication, “Guided Structure-Aligned Segmentation of Volumetric Data” at the International Symposium on Visual Computing (ISVC) 2015 conference, held Dec. 14-16, 2015 in Las Vegas, NV. The paper, authored by Michelle Holloway of Washington University in St. Louis, Anahita Sanandaji of Oregon State University, Deniece Yates of Oregon State University, Amali Krigger of Oregon State University, Ross Sowell of Cornell College, Ruth West of...

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