Medical Imaging Technology
Online ISSN : 2185-3193
Print ISSN : 0288-450X
ISSN-L : 0288-450X
研究論文
Feature Extraction from Non-Linear Scale Spaces Using the Guided Filter for Fast Robust Organ Tracking in Water-Filled Laparoendoscopic Surgery
Mika KONTTORyoichi NAKAMURA
著者情報
ジャーナル フリー
電子付録

2020 年 38 巻 3 号 p. 116-125

詳細
抄録

In this paper, a local feature extraction method based on fast image guided filtering for organ tracking in Water-filled Laparoendoscopic Surgery (WaFLES) is presented. Robust feature extraction and matching is important for feature based tracking and 3d-reconstruction techniques. We created a non-linear scale space and extracted Hessian determinant features, described with MLDB-descriptor that performed robustly in WaFLES images, outperforming Akaze in matching. We showed that non-linear scale space methods, especially our method, are most robust for WaFLES, over de facto SIFT, SURF and ORB methods. It was demonstrated that the scale space could be created more efficiently using fast guided filtering over non-explicit diffusion. We are bringing these techniques closer to real-time capability in simpler hardware, without sacrificing performance.

著者関連情報
© 2020 The Japanese Society of Medical Imaging Technology
前の記事 次の記事
feedback
Top