Feature Based Fusion of Multimodal Medical Image Slices with Combined Transforms

Kavitha, C.T.; Chellamuthu, C.

doi:10.2174/1573405612999160510145716

Cited by 1 publication

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“…Furthermore, temporal surface of phantom (or patient) is separated in a feature extraction step. 3D surface segmentation step, made 3D shape of outer CT layer from CT slice's [37].…”

Section: Methodsmentioning

confidence: 99%

Registration and fusion of 3D surface data from CT and ToF camera for position verification in radiotherapy

et al. 2019

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The purpose of this study is to introduce a low-cost method for verification of patient positioning before and during irradiation in radiotherapy. The experiments strategy is implemented by using a phantom like a human head in two modes: with and without thermoplastic masks. Radiotherapy is an effective clinical option for topical tumors treatment. Ability to the monitoring and control the patient's position during treatment is among the important items in radiotherapy. We registered to modality of 3D surface image in point cloud format, dynamic 3D image of time-of-flight camera (includes outer shape of head) and static 3D image of CT slice sectional by coherent point drift algorithm. Accuracy of 3D surface registration was calculated by average symmetrical surface distances (ASD) that it is a new method based on surface distance. The mean ASD calculated for rotation around X and Y axes of phantom is 2.62 ± 0.97 mm with immobilized thermoplastic mask and accuracy be increased to 1.69 ± 0.88 mm in non-thermoplastic mode. By performing paired T tests for ASDs, it was found that the use of a thermoplastic mask does not make a significant difference in the data acquisition. By developing this research to image fusion of that's 3D data sets, we will design to augmented reality in radiotherapy for verification of treatment planning and compare it with the electronic portal imaging device.

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“…Furthermore, temporal surface of phantom (or patient) is separated in a feature extraction step. 3D surface segmentation step, made 3D shape of outer CT layer from CT slice's [37].…”

Section: Methodsmentioning

confidence: 99%