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
Number of pages8
ISBN (Electronic)9781510633971
Publication statusPublished - 2020
EventMedical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling - Houston, United States
Duration: 16 Feb 202019 Feb 2020


ConferenceMedical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling
CountryUnited States

    Research areas

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

ID: 73439123