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Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation
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Learning-based keypoint registration for fetoscopic mosaicking.

Alessandro Casella1,2,3, Sophia Bano4, Francisco Vasconcelos3

  • 1Department of Advanced Robotics, Istituto Italiano di Tecnologia, Genoa, Italy.

International Journal of Computer Assisted Radiology and Surgery
|December 8, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a new AI framework to improve surgical visualization for twin-to-twin transfusion syndrome (TTTS) by expanding the field of view during fetoscopic laser ablation. The AI enhances surgical precision and provides better context awareness for surgeons.

Keywords:
Deep learningFetal surgeryFetoscopyMosaickingSelf-supervisedTwin-to-twin transfusion syndrome

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Area of Science:

  • Medical Imaging
  • Surgical Technology
  • Computational Biology

Background:

  • Twin-to-twin transfusion syndrome (TTTS) involves abnormal placental vascular connections causing unequal fetal blood flow.
  • Current surgical treatment uses fetoscopic laser ablation, but limited field of view hinders precise identification of abnormal anastomoses.

Purpose of the Study:

  • To develop a learning-based framework for in vivo fetoscopy frame registration to expand the surgical field of view.
  • To address the challenge of identifying abnormal vascular anastomoses during TTTS surgery.

Main Methods:

  • A novel framework utilizing a learning-based keypoint proposal network for fetoscopy frame registration.
  • An encoding strategy to filter irrelevant keypoints using semantic image segmentation and inconsistent homographies.

Main Results:

  • The proposed framework was validated on intraoperative fetoscopy sequences from six TTTS surgeries.
  • Performance was compared against a state-of-the-art algorithm relying on placenta vessel segmentation.

Conclusions:

  • The developed framework demonstrates superior performance compared to existing methods.
  • This advancement enables robust mosaicking, enhancing surgeon's situational awareness during TTTS interventions.