# Optical Flow-Based Extraction of Breathing Signal from Cone Beam CT Projections
## 2 Literature Review
### Image-Based Methods
#### 2.6.3 Markerless (Amplitude/Phase) Binning  
Respiratory motion-management methods such as surface markers, abdominal compression, breath-hold, fiducial marker and diaphragm tracking face certain limitations. While it is not very evident how well a marker placed on patient's chest correlates with a tumor motion within the lung, fiducial markers implanted near the tumor site can cause certain health risks. Breath-hold and abdominal-compression methods try to minimize the motion, but cause discomfort to the patient. To overcome the limitations caused by these methods, a shift towards markerless image-based methods is needed, to estimate the breathing motion and reconstruct motion-compensated 4-dimensional images. Several studies are found within the literature that have highlighted the potential of using markerless methods. [PERSON] et al. [18] designed an algorithm using an improved 3D KLT (Kanade-Lucas-Tomasi) tracker to estimate lung motion from 4D CT scans. The tracker identified feature points from the projections based on change in image gradient or intensity. It was observed that the feature points near the inferior area of the lung show more displacement and provide better tracking accuracy as compared to feature points in the superior lung region. The tracking accuracy is also significantly reduced with higher rotation angle, going from an accuracy of 79.6% at 2 degrees to 15.8% at 10 degrees. [PERSON] et al. [19] investigated the feasibility of a novel markerless technique to sort CBCT projections for 4D reconstruction. As per the Fourier transform (FT) principle, the FT image magnitude shows how much a certain frequency component is exhibited in an image; on the other hand, the phase shows the position of that specific frequency in the image. Projections associated with the peak inhale phase were identified with both amplitude and phase FT methods. The methods were tested on two phantom and three clinical datasets. For the FT phase method, the average phase shift compared to manual ground-truth for phantom 1 with 3 s breathing cycle was 1.8%, and for phantom 2 with 6 s breathing cycle it was 3.9%. The clinical datasets resulted in a difference of 2.9%, 5.0% and 3.8% for the three patients, respectively. The magnitude FT method resulted in a difference of 2.1% and 4.0% for the two phantoms and 2.9%, 5.3% and 3.5% for the three patients. The observed phase difference and quality reconstructed images using both methods show the feasibility of Fourier transform methods. More investigation on patient datasets attained at slow gantry rotation is required to be performed, to fully understand the potential of the proposed technique. [PERSON] et al. [20] developed a markerless technique for the extraction of the respiratory signal called local intensity feature tracking (LIFT). Firstly, feature points were extracted at evenly distanced pixels, excluding the pixels representing the diaphragm region. The feature points were then tracked across the projection datasets and motion trajectory was formed. Trajectories experiencing oscillatory behavior similar to the respiratory pattern were clustered, thereby retrieving the 3D lung movement. A mean phase shift of 1.68 projections and 1.78 projections was observed with LIFT, in comparison to ground-truth obtained from diaphragm tracking and internal marker tracking, respectively. [PERSON] et al. [21] suggested the use of the optical-flow technique with linear and non-linear dimensionality reduction to extract the respiratory signal. Implementation of the method on patient data resulted in a mean phase shift of 3.77 \(\pm\) 1.31, 3.59 \(\pm\) 2.44, 3.83 \(\pm\) 2.65 for the three patients 1, 2 and 3, respectively. [PERSON] et al. [22] presented an image registration-based projection binning (IRPB) method for sorting 4D CBCT projections. The proposed method involved identification of feature points in accordance with changes in intensity inside a rounded pixel mask.