Real-time tumor tracking in B-mode images using respiratory signal and deformed liver models

Youngkyoo Hwang; Young-Taek Oh; Jung-Bae Kim; Won-Chul Bang; Heesae Lee; James D.K. Kim; Chang Yeong Kim

doi:10.1117/12.2007857

15 March 2013 Real-time tumor tracking in B-mode images using respiratory signal and deformed liver models

Youngkyoo Hwang, Young-Taek Oh, Jung-Bae Kim, Won-Chul Bang, Heesae Lee, James D.K. Kim, Chang Yeong Kim

Proceedings Volume 8671, Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling; 86711Q (2013) https://doi.org/10.1117/12.2007857
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

Tumor tracking is very important to deal with a cancer in a moving organ in clinical applications such as radiotherapy, HIFU etc. Respiratory monitoring systems are widely used to find location of the cancers in the organs because respiratory signal is highly correlated with the movement of organs such as the lungs and liver. However the conventional respiratory system doesn’t have enough accuracy to track the location of a tumor as well as they need additional effort or devices to use. In this paper, we propose a novel method to track a liver tumor in real time by extracting respiratory signals directly from B-mode images and using a deformed liver model generated from CT images of the patient. Our method has several advantages. 1) There is no additional radiation dose and is cost effective due to use of an ultrasound device. 2) A high quality respiratory signal can be directly extracted from 2D images of the diaphragm. 3) Using a deformed liver model to track a tumor’s 3D position, our method has an accuracy of 3.79mm in tracking error.

Citation Download Citation

Youngkyoo Hwang, Young-Taek Oh, Jung-Bae Kim, Won-Chul Bang, Heesae Lee, James D.K. Kim, and Chang Yeong Kim "Real-time tumor tracking in B-mode images using respiratory signal and deformed liver models", Proc. SPIE 8671, Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling, 86711Q (15 March 2013); https://doi.org/10.1117/12.2007857

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