Improvement of flattenability using particle swarm optimizer for surface unfolding in bolus shaping
- PDF / 4,742,636 Bytes
- 19 Pages / 595.276 x 790.866 pts Page_size
- 21 Downloads / 159 Views
Improvement of flattenability using particle swarm optimizer for surface unfolding in bolus shaping Rui Li1 · Qingjin Peng1 · Harry Ingleby2 · David Sasaki2 Received: 3 December 2019 / Accepted: 12 August 2020 © Springer Nature Switzerland AG 2020
Abstract Bolus, formed by a sheet of material, covers on tumors of patient skins to generate the desired dose distribution in a process of the high-energy radiotherapy. The existing methods of bolus shaping use a manual process to cut the commercial material into the shape, which can cause air gaps between the patient skin surface and bolus in the reduced effect of cancer care treatment. A method of automatic bolus shaping can improve the accuracy and reduce air gaps of bolus shaping, which uses a process of first segmenting 3D patient skin surface models into several patches and then unfolding the patches into 2D patterns for material cutting before folding the cut sheet into the bolus. However, air gaps between the bolus and patient skin surface cannot be directly evaluated to find the bolus accuracy. This paper proposes a method to improve model flattenability and evaluate the air gaps using a particle swarm optimizer (PSO). A 3D surface shape is unfolded only if the air gap and surface flattenability meet the requirement of accuracy. Otherwise, the surface will be segmented into several patches to improve the flattenability and reduce air gaps. The objective and constraint are identified to search for an optimal solution for the 3D surface with a high flattenability. A strategy of the dimension reduction is proposed for the selection of local nodes on a meshed surface to increase the searching efficiency of surface flattenability. A local node selection based PSO (L-PSO) method is developed to search for the optimal solution. The proposed method is verified in two case studies of bolus shaping. Keywords Surface optimization · Flattenability · Bolus · Particle swarm optimizer (PSO)
1 Introduction A bolus is used to cover patient skin surfaces during the high-energy radiotherapy for the desired dose distribution [1]. In the clinic, commercial materials are used in bolus shaping by cutting the material into the shape of a targeted body area to cover the area. For some irregular body surfaces such as knee, nose, and elbow, the manual process of bolus shaping will cause air gaps between the human surface and bolus, which reduces the therapeutic effect [2]. Inspiring by applications of digital 3D technologies in the garment manufacturing process, a 3D-to-2D and
2D-to-3D process was developed for the bolus shaping to reduce air gaps and increase shaping efficiency [3, 4]. Human surface data are obtained using a 3D scanner to build a mesh surface that is a kind of discrete surfaces and most of them are non-developable that cannot be unfolded into 2D patches without deformation and distortion. The 3D triangular mesh surface is segmented into several patches to increase flattenability and then to be unfolded into 2D patches for shaping bolus. Commercial materials can then
Data Loading...
