Intraoperative Tumor Localization Using Sweeping Palpation in Robot-Assisted Minimally Invasive Surgery (RMIS)
Jeongbin Hong, Yunjeong Lee, Youngjun Ryu, Hyoryong Lee, Joowon Park, Sukho Park
AI summary
Problem
Robot-assisted minimally invasive surgery lacks tactile feedback, making it difficult to detect tumor edges intraoperatively. Existing robotic palpation methods struggle with precise edge detection on curved tissue surfaces and rely heavily on preoperative imaging that degrades due to organ deformation.
Approach
The method reconstructs tissue surface geometry without medical images, performs sweeping palpation to generate a contact force map, and applies a Laplacian edge detection algorithm to force data to pinpoint tumor boundaries.
Key results
- Image-free 3D surface reconstruction on curved tissues via Point2Mesh deep learning
- Accurate tumor centroid estimation using mean-shift clustering on force maps
- Precise tumor edge detection through Laplacian analysis of sigmoid-fitted force profiles
- Validated across planar, curved, and kidney phantom models
Why it matters
Provides surgeons with reliable, real-time tactile tumor boundary mapping during minimally invasive procedures, reducing reliance on error-prone preoperative imaging.
Abstract
Robot-assisted minimally invasive surgery (RMIS) provides superior visualization, precision, and flexibility, and it has gained recognition as a technology that enhances therapeutic outcomes, particularly in tumor resection. However, this technology has a limitation in that it predominantly relies on visual feedback, making it challenging for surgeons to accurately detect the location and edges of tumors during surgery. To address this issue, robotic palpation methods have been actively studied. Among these, the sweeping palpation method has the advantage of rapidly exploring a broad region. Nevertheless, conventional sweeping palpation methods can only roughly identify the tumor’s location and are limited in detecting tumor edges with precision. In this study, we introduce a novel sweeping palpation method to overcome the limitations of conventional sweeping palpation in RMIS and propose a precise tumor localization method based on this approach. The proposed method involves performing sweeping palpation on the tissue surface using the tip of the robotic end effector while utilizing a Laplacian edge detection algorithm to detect abrupt changes in contact force. This method reduces the reliance on preoperative imaging and enables tumor localization to be performed within a single robotic system. To validate the proposed tumor localization method, we conducted three phantom experiments and ex vivo experiment. These validations demonstrate the potential of our proposed method to contribute to precise tumor resection and the establishment of effective treatment plans.