Markerless estimation of patient orientation, posture and pose using range and pressure imaging: For automatic patient setup and scanner initialization in tomographic imaging

Beitrag in einer Fachzeitschrift
(Originalarbeit)


Details zur Publikation

Autor(en): Grimm R, Bauer S, Sukkau J, Hornegger J, Greiner G
Zeitschrift: International Journal of Computer Assisted Radiology and Surgery
Verlag: Springer Verlag (Germany)
Jahr der Veröffentlichung: 2012
Band: 7
Heftnummer: 6
Seitenbereich: 921-929
ISSN: 1861-6410


Abstract


Purpose In diagnostic tomographic imaging, patient setup and scanner initialization is a manual, tedious procedure in clinical practice. A fully-automatic detection of the patient's position, orientation, posture and pose on the patient table holds great potential for optimizing this part of the imaging workflow. We propose a markerless framework that is capable of extracting this information within seconds from either range imaging (RI) or pressure imaging (PI) data. Methods The proposed method is composed of three stages: First, the position and orientation of the reclined patient are determined. Second, the patient's posture is classified. Third, based on the estimated orientation and posture, an approximate body pose is recovered by fitting an articulated model to the observed RI/PI data. Being a key issue for clinical application, our approach does not require an initialization pose. Results In a case study on real data from 16 subjects, the performance of the proposed system was evaluated quantitatively with a 3-D time-of-flight RI camera and a pressure sensing mattress (PI). The patient orientation was successfully determined for all subjects, independent of the modality. At the posture recognition stage, our method achieved mean classification rates of 79.4% for RI and 95.5% for PI data, respectively. Concerning the approximate body pose estimation, anatomical body landmarks were localized with an accuracy of ±5.84 cm (RI) and ±5.53 cm (PI). Conclusions The results indicate that an estimation of the patient's position, orientation, posture and pose using RI and PI sensors, respectively, is feasible, and beneficial for optimizing the workflow in diagnostic tomographic imaging. Both modalities achieved comparable pose estimation results using different models that account for modality-specific characteristics. PI outperforms RI in discriminating between prone and supine postures due to the distinctive pressure distribution of the human body. © CARS 2012.



FAU-Autoren / FAU-Herausgeber

Bauer, Sebastian
Lehrstuhl für Informatik 5 (Mustererkennung)
Greiner, Günther Prof. Dr.
Lehrstuhl für Informatik 9 (Graphische Datenverarbeitung)
Grimm, Robert
Lehrstuhl für Informatik 5 (Mustererkennung)
Hornegger, Joachim Prof. Dr.-Ing.
Lehrstuhl für Informatik 5 (Mustererkennung)


Autor(en) der externen Einrichtung(en)
Siemens AG


Zitierweisen

APA:
Grimm, R., Bauer, S., Sukkau, J., Hornegger, J., & Greiner, G. (2012). Markerless estimation of patient orientation, posture and pose using range and pressure imaging: For automatic patient setup and scanner initialization in tomographic imaging. International Journal of Computer Assisted Radiology and Surgery, 7(6), 921-929. https://dx.doi.org/10.1007/s11548-012-0694-5

MLA:
Grimm, Robert, et al. "Markerless estimation of patient orientation, posture and pose using range and pressure imaging: For automatic patient setup and scanner initialization in tomographic imaging." International Journal of Computer Assisted Radiology and Surgery 7.6 (2012): 921-929.

BibTeX: 

Zuletzt aktualisiert 2018-08-08 um 19:10