Summary of A Fourier-enhanced Multi-modal 3d Small Object Optical Mark Recognition and Positioning Method For Percutaneous Abdominal Puncture Surgical Navigation, by Zezhao Guo (1) et al.
A Fourier-enhanced multi-modal 3D small object optical mark recognition and positioning method for percutaneous abdominal puncture surgical navigation
by Zezhao Guo, Yanzhong Guo, Zhanfang Zhao
First submitted to arxiv on: 13 Apr 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI); Robotics (cs.RO)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed method is a multi-modal 3D small object medical marker detection approach that identifies the center of a small single ring as the needle insertion point. This novel method leverages Fourier transform enhancement technology to augment the dataset, enrich image details, and enhance network capability. The approach involves extracting the Region of Interest (ROI) from both enhanced and original images, generating a mask map, obtaining the ROI point cloud contour fitting through registration, and employing Tukey loss for optimal precision. This method achieves high-precision and high-stability positioning, enabling the positioning of any needle insertion point. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A new way to help doctors do surgery is being developed. Right now, it’s hard to find the right spot on the body to put a special needle in during operations. The problem is that there aren’t many clear points on the skin that can be used as landmarks. A team of researchers came up with an innovative solution: a method that uses 3D technology and light to detect small objects, like rings, to guide the doctor’s hand to the correct spot. This approach can help make surgery more accurate and precise. |
Keywords
» Artificial intelligence » Mask » Multi modal » Precision
