Soft Tissue Monitoring of the Surgical Field: Detection and Tracking of Breast Surface Deformations.

Objective: Deformable object tracking is common in the computer vision field, with applications typically focusing on nonrigid shape detection and usually not requiring specific three-dimensional point localization. In surgical guidance however, accurate navigation is intrinsically linked to precise correspondence of tissue structure. This work presents a contactless, automated fiducial acquisition method using stereo video of the operating field to provide reliable three-dimensional fiducial localization for an image guidance framework in breast conserving surgery.

Methods: On n = 8 breasts from healthy volunteers, the breast surface was measured throughout the full range of arm motion in a supine mock-surgical position. Using hand-drawn inked fiducials, adaptive thresholding, and KAZE feature matching, precise three-dimensional fiducial locations were detected and tracked through tool interference, partial and complete marker occlusions, significant displacements and nonrigid shape distortions.

Results: Compared to digitization with a conventional optically tracked stylus, fiducials were automatically localized with 1.6 ± 0.5 mm accuracy and the two measurement methods did not significantly differ. The algorithm provided an average false discovery rate <0.1% with all cases' rates below 0.2%. On average, 85.6 ± 5.9% of visible fiducials were automatically detected and tracked, and 99.1 ± 1.1% of frames provided only true positive fiducial measurements, which indicates the algorithm achieves a data stream that can be used for reliable on-line registration.

Conclusions: Tracking is robust to occlusions, displacements, and most shape distortions.

Significance: This work-flow friendly data collection method provides highly accurate and precise three-dimensional surface data to drive an image guidance system for breast conserving surgery.