Transformation optimization and image blending for 3D liver ultrasound series stitching

Yuanyuan Sun, Taygun Kekec, Adriaan Moelker, Wiro J. Niessen, Theo Van Walsum

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Abstract

We propose a consistent ultrasound volume stitching framework, with the intention to produce a volume with higher image quality and extended field-of-view in this work. Directly using pair-wise registrations for stitching may lead to geometric errors. Therefore, we propose an approach to improve the image alignment by optimizing a consistency metric over multiple pairwise registrations. In the optimization, we utilize transformed points to effectively compute a distance between rigid transformations. The method has been evaluated on synthetic, phantom and clinical data. The results indicate that our transformation optimization method is effective and our stitching framework has a good geometric precision. Also, the compound images have been demonstrated to have improved CNR values.

Original languageEnglish
Title of host publicationProceedings of SPIE : Medical Imaging 2020
Subtitle of host publicationImage-Guided Procedures, Robotic Interventions, and Modeling
EditorsBaowei Fei, Cristian A. Linte
PublisherSPIE
Number of pages8
Volume11315
ISBN (Electronic)9781510633971
DOIs
Publication statusPublished - 2020
EventMedical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling - Houston, United States
Duration: 16 Feb 202019 Feb 2020

Conference

ConferenceMedical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling
Country/TerritoryUnited States
CityHouston
Period16/02/2019/02/20

Keywords

  • 3D Ultrasound
  • Liver
  • Stitching
  • Ultrasound guided intervention

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