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Joint ToF Image Denoising and Registration with a CT Surface in Radiation Therapy
| Citations: | 6 - 6 self |
BibTeX
@MISC{Bauer_jointtof,
author = {Sebastian Bauer and Benjamin Berkels and Joachim Hornegger and Martin Rumpf},
title = {Joint ToF Image Denoising and Registration with a CT Surface in Radiation Therapy},
year = {}
}
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Abstract
Abstract. The management of intra-fractional respiratory motion is becoming increasingly important in radiation therapy. Based on in advance acquired accurate 3D CT data and intra-fractionally recorded noisy timeof-flight (ToF) range data an improved treatment can be achieved. In this paper, a variational approach for the joint registration of the thorax surface extracted from a CT and a ToF image and the denoising of the ToF image is proposed. This enables a robust intra-fractional full torso surface acquisition and deformation tracking to cope with variations in patient pose and respiratory motion. Thereby, the aim is to improve radiotherapy for patients with thoracic, abdominal and pelvic tumors. The approach combines a Huber norm type regularization of the ToF data and a geometrically consistent treatment of the shape mismatch. The algorithm is tested and validated on synthetic and real ToF/CT data and then evaluated on real ToF data and 4D CT phantom experiments. 1
Keyphrases
radiation therapy joint tof image denoising ct surface tof image improved treatment variational approach shape mismatch respiratory motion thorax surface joint registration ct phantom experiment intra-fractional respiratory motion real tof data consistent treatment patient pose ct data huber norm type regularization range data pelvic tumor tof data real tof ct data recorded noisy timeof-flight
