Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 142 tok/s
Gemini 2.5 Pro 48 tok/s Pro
GPT-5 Medium 32 tok/s Pro
GPT-5 High 26 tok/s Pro
GPT-4o 93 tok/s Pro
Kimi K2 201 tok/s Pro
GPT OSS 120B 420 tok/s Pro
Claude Sonnet 4.5 36 tok/s Pro
2000 character limit reached

Initialize globally before acting locally: Enabling Landmark-free 3D US to MRI Registration (1806.04368v1)

Published 12 Jun 2018 in eess.IV and cs.CV

Abstract: Registration of partial-view 3D US volumes with MRI data is influenced by initialization. The standard of practice is using extrinsic or intrinsic landmarks, which can be very tedious to obtain. To overcome the limitations of registration initialization, we present a novel approach that is based on Euclidean distance maps derived from easily obtainable coarse segmentations. We evaluate our approach quantitatively on the publicly available RESECT dataset and show that it is robust regarding overlap of target area and initial position. Furthermore, our method provides initializations that are suitable for state-of-the-art nonlinear, deformable image registration algorithm's capture ranges.

Citations (8)

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.