Table 2.
Properties of the marker segmentation algorithms discussed in section 2.2.1.
| Method | Marker shape | Site (patient number) | Image type | Template generation | Manual input needed | Automatic error detection |
|---|---|---|---|---|---|---|
| Fledelius et al (2014) | Cylindrical | Liver (13) | CBCT, kV, MV | Automatic | No | Yes—rejected segmentation |
| Mao et al (2008) | Spherical, Cylindrical | Prostate (5) | kV, MV | Automatic | No | Noa |
| Tang et al (2007) | Cylindrical | Liver (2) | kV | Automatic (from library) | Yes (initialization) | Yes—terminates segmentation |
| Marchant et al (2012) | Cylindrical | Pancreas (2), prostate (1) | CBCT | Gaussian kernels | Yes (initialization) | Noa |
| Regmi et al (2014) | Arbitrary (Visicoil), Cylindrical | Pancreas (4), Gastrointestinal junction (6), lungs (1) | CBCT | From breath-hold CT | Yes (template generation pre-treatment) | No |
| Bertholet et al (2017) | Arbitrary (Visicoil), Cylindrical | Thorax (12), Abdomen (28) | CBCT | Automatic | No | Yes—rejected segmentation |
| Campbell et al (2017b)b | Cylindrical marker group | Pancreas (15) | CBCT | Automatic | No | Noa |
| Lin et al (2013) | Cylindrical | Prostate (2) | MV | No | Yes (manual selection of training sample at fraction 1) | No |
| Wan et al (2016)b | Arbitrary (visicoil, embolization coil), cylindrical (gold, Calypso) | Abdomen (34), Lung (5) | CBCT | No | No | No |
a
Methods designed to have a 100% detection rate.
b
Not fully demonstrated in real-time.