Image-based motion detection: using the concept of weighted directional descriptors.

Abstract

The use of image guidance in medical applications is constantly growing because of its tremendous impact on the future of health care. Although image-based tissue tracking has been thoroughly explored in the academic literature for years, it has not yet matured to become widely accepted by clinicians. Undetected tissue movements in image-based clinical procedures may cause safety and efficacy difficulties. We introduce an image-based approach for detecting tissue movements during clinical procedures. Our method has been validated in more than 600 true clinical cases. The results show that our algorithm agrees with an expert analysis in 98% of the cases, showing zero events of false alarms and zero events of undetected motion. The results show that the approach provides a clinically ready motion detection algorithm. These robust results are achieved by introducing the concept of weighted directional descriptors (WDDs). The technique analyzes the directivity and confidence level of each anatomical feature and uses it to weight local inputs resulting in a robust motion vector. The robustness is further increased by a novel preprocess that screens out features that may be misleading or are repeated in the adjacent search zone. The technique meets the requirements, as defined by our clinicians, and is now integrated in true medical systems. In particular, our approach has been uniquely developed and integrated into a clinical product. ExAblate is the first Food and Drug Administration (FDA)-approved magnetic resonance (MR)-guided noninvasive surgical device using focused ultrasound therapy. It is used in commercial clinics and in leading medical academic research institutions, attesting to the success of our method and its practical clinical value.