Name
Abstract | ||
|---|---|---|
To ensure precise tumor irradiation in radiotherapy a stable breathing pattern is mandatory as tumors are moving due to respiratory motion. Consequentially, irregularities of respiratory patterns have to be detected immediately. The causal motion of tissue also difiers due to difierent physiological types of respiration, e.g., chest- or abdominal breathing. Currently used devices to measure respiratory motion do not incorporate complete surface deformations. Instead only small regions of interest are considered. Thereby, valuable information to detect difierent breathing patterns and types are lost. In this paper we present a system that uses a novel camera sensor called Time-of-Flight (ToF) for auto- matic classiflcation and veriflcation of breathing patterns. The proposed algorithm calculates multiple volume signals of difierent anatomical re- gions of the upper part of the patient's body. Therefore disjoint regions of interest are deflned for both, the patient's abdomen and thorax. Us- ing the calculated volume signals the type of respiration is determined in real-time by computing an energy coe-cient. Changing breathing patterns can be visualized using a 2-D histogram, which is also used to classify and detect abnormal breathing phases. We evaluated the pro- posed method on flve persons and obtained a reliable difierentation of chest- and abdominal breathing in all test cases. Furthermore, we could show that the introduced 2-D histogram enables an accurate determina- tion of changing breathing patterns. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-540-93860-6_52 | Bildverarbeitung für die Medizin |
Keywords | Field | DocType |
time of flight,region of interest,real time | Histogram,Image sensor,Pattern recognition,Respiratory motion,Simulation,Computer science,Breathing patterns,Abnormal breathing,Artificial intelligence,Breathing,Diaphragmatic breathing | Conference |
Citations | PageRank | References |
1 | 0.40 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kerstin Müller | 1 | 7 | 4.36 |
| Christian Schaller | 2 | 42 | 6.35 |
| Jochen Penne | 3 | 168 | 14.87 |
| Joachim Hornegger | 4 | 1734 | 190.62 |