  The purpose of this paper is to help the anesthesiologist to find the
epidural depth automatically to make the first attempt to enter the path of the
needle into the patient's body while it is clogged with bone and avoid causing
a puncture in the surrounding areas of the patient`s back. In this regard, a
morphology-based bone enhancement and detection followed by a
Ramer-Douglas-Peucker algorithm and Hough transform is proposed. The proposed
algorithm is tested on synthetic and real ultrasound images of laminar bone,
and the results are compared with the template matching based Ligamentum Flavum
(LF) detection method. Results indicate that the proposed method can faster
detect the diagonal shape of the laminar bone and its corresponding epidural
depth. Furthermore, the proposed method is reliable enough providing
anesthesiologists with real-time information while an epidural needle insertion
is performed. It has to be noted that using the ultrasound images is to help
anesthesiologists to perform the blind injection, and due to quite a lot of
errors occurred in ultrasound-imaging-based methods, these methods can not
completely replace the tissue pressure-based method. And in the end, when the
needle is injected into the area (dura space) measurements can only be trusted
to the extent of tissue resistance. Despite the fairly limited amount of
training data available in this study, a significant improvement of the
segmentation speed of lumbar bones and epidural depth in ultrasound scans with
a rational accuracy compared to the LF-based detection method was found.
