Real-Time Automatic Artery Segmentation, Reconstruction and Registration for Ultrasound-Guided Regional Anaesthesia of the Femoral Nerve

ABSTRACT:

The goal is to create an assistant for ultrasound-guided femoral nerve block. By segmenting and visualizing the important structures such as the femoral artery, we hope to improve the success of these procedures. This article is the first step towards this goal and presents novel real-time methods for identifying and reconstructing the femoral artery, and registering a model of the surrounding anatomy to the ultrasound images. The femoral artery is modelled as an ellipse. The artery is first detected by a novel algorithm which initializes the artery tracking. This algorithm is completely automatic and requires no user interaction. Artery tracking is achieved with a Kalman filter. The 3D artery is reconstructed in real-time with a novel algorithm and a tracked ultrasound probe. A mesh model of the surrounding anatomy was created from a CT dataset. Registration of this model is achieved by landmark registration using the centerpoints from the artery tracking and the femoral artery centerline of the model. The artery detection method was able to automatically detect the femoral artery and initialize the tracking in all 48 ultrasound sequences. The tracking algorithm achieved an average dice similarity coefficient of 0.91, absolute distance of 0.33 mm, and Hausdorff distance 1.05 mm. The mean registration error was 2.7 mm, while the average maximum error was12.4 mm. The average runtime was measured to be 38,8,46 and 0.2 milliseconds for the artery detection, tracking, reconstruction and registration methods respectively.

PROJECT OUTPUT VIDEO:

EXISTING SYSTEM:

• Several methods for segmentation of the cross-section of vessels in 2D ultrasound have been reported, using methods such as level sets, fuzzy c-means clustering and evolutionary algorithms. These methods focus on segmenting a single image. However, in this work the goal is to segment the femoral artery in real-time on a sequence of ultrasound images.

PROPOSED SYSTEM:

• A real-time automatic artery detection method. This method eliminates the need for manual initialization .

• A real-time vessel tracking method of the femoral artery similar to the approaches. While their methods use two Kalman filters, one for estimating the position of the vessel and another to estimate the shape, the proposed method uses only one Kalman filter resulting in a simpler method.

• The proposed method can also reconstruct bifurcations.

• A real-time vessel registration method which registers a model of the femoral region anatomy to the ultrasound images. The method is automatic and provides anatomical reference to the operator.

ADVANTAGES OF PROPOSED SYSTEM:

• The presented methods are able to automatically and accurately track the femoral artery in ultrasound images and use this to reconstruct the artery in 3D and register it to a model of the surrounding anatomy in real-time.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS:

• System          : Pentium Dual Core.

• Hard Disk      : 120 GB.

• Monitor          : 15’’ LED

• Input Devices : Keyboard, Mouse

• Ram                : 1GB.

SOFTWARE REQUIREMENTS:

• Operating system : Windows 7.

• Coding Language : MATLAB

• Tool                      : MATLAB R2013A

REFERENCE:

Erik Smistad* and Frank Lindseth, “Real-Time Automatic Artery Segmentation, Reconstruction and Registration for Ultrasound-Guided Regional Anaesthesia of the Femoral Nerve”, IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 35, NO. 3, MARCH 2016.