• Journal of KIISE:Software and Applications
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• v.37 no.1
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• pp.9-18
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• 2010

This paper proposes a deformable registration method using a demon algorithm for aligning the lungs between end-exhale and end-inhale CT scans. The lungs are globally aligned by affine transformation and locally deformed by a demon algorithm. The use of floating gradient force allows a fast convergence in the lung regions with a weak gradient of the reference image. The active-cell-based demon algorithm helps to accelerate the registration process and reduce the probability of deformation folding because it avoids unnecessary computation of the displacement for well-matched lung regions. The performance of the proposed method was evaluated through comparisons of methods that use a reference gradient force or a combined gradient force as well as methods with and without active cells. The results show that the proposed method can accurately register lungs with large deformations and can reduce the processing time considerably.

• Progress in Medical Physics
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• v.25 no.3
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• pp.167-175
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• 2014

The purpose of this study is to evaluate the variation of the dose which is delivered to the patients with glottis cancer under IMRT (intensity modulated radiation therapy) by using the 3D registration with CBCT (cone beam CT) images and the DIR (deformable image registration) techniques. The CBCT images which were obtained at a one-week interval were reconstructed by using B-spline algorithm in DIR system, and doses were recalculated based on the newly obtained CBCT images. The dose distributions to the tumor and the critical organs were compared with reference. For the change of volume depending on weight at 3 to 5 weeks, there was increased of 1.38~2.04 kg on average. For the body surface depending on weight, there was decreased of 2.1 mm. The dose with transmitted to the carotid since three weeks was increased compared be more than 8.76% planned, and the thyroid gland was decreased to 26.4%. For the physical evaluation factors of the tumor, PITV, TCI, rDHI, mDHI, and CN were decreased to 4.32%, 5.78%, 44.54%, 12.32%, and 7.11%, respectively. Moreover, $D_{max}$, $D_{mean}$, $V_{67.50}$, and $D_{95}$ for PTV were increased or decreased to 2.99%, 1.52%, 5.78%, and 11.94%, respectively. Although there was no change of volume depending on weight, the change of body types occurred, and IMRT with the narrow composure margin sensitively responded to such a changing. For the glottis IMRT, the patient's weight changes should be observed and recorded to evaluate the actual dose distribution by using the DIR techniques, and more the adaptive treatment planning during the treatment course is needed to deliver the accurate dose to the patients.

• Journal of radiological science and technology
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• v.35 no.2
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• pp.173-181
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• 2012

The aim of this study is to compare the geometric characteristics of the lung tumor, such as tumor centroid, HU change relative to breath phase, depending on tumor location and adhesion using 4DCT and deformable image registration program (MIMVista). The Y axis change was most significant and the mean Y axis centroid fluctuation was $7.32{\pm}6.88mm$ in lower lung tumor. The mean HU variation in lower lung mass has changed more than other locations, and its mean HU variation was $7.7{\pm}4.97%$ and non-adhered mass was more changed. Correlation for the mass volume between 3DCT and MIP was very high and its coefficient was 0.998. The effect of tumor location, adhesion and diaphragm excursion to geometric uncertainties was analyzed by linear regression model, it was influenced to mass deformation and geometrical variation so much except diaphragm excursion. but intra-fractional and inter-patient's uncertainties were great, so it couldn't find any exact deformation trend.

• Journal of Radiation Protection and Research
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• v.44 no.3
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• pp.103-109
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• 2019

Background: Four-dimensional computed tomographic (4DCT) images are increasingly used in clinic with the growing need to account for the respiratory motion of the patient during radiation treatment. One of the reason s that makes the dose evaluation using 4DCT inaccurate is a change of the patient respiration during the treatment session, i.e., intrafractional uncertainty. Especially, when the amplitude of the patient respiration is greater than the respiration range during the 4DCT acquisition, such an organ motion from the larger respiration is difficult to be represented with the 4DCT. In this paper, the method to generate images expecting the organ motion from a respiration with extended amplitude was proposed and examined. Materials and Methods: We propose a method to generate extra-phase images from a given set of the 4DCT images using deformable image registration (DIR) and linear extrapolation. Deformation vector fields (DVF) are calculated from the given set of images, then extrapolated according to respiratory surrogate. The extra-phase images are generated by applying the extrapolated DVFs to the existing 4DCT images. The proposed method was tested with the 4DCT of a physical 4D phantom. Results and Discussion: The tumor position in the generated extra-phase image was in a good agreement with that in the gold-standard image which is separately acquired, using the same 4DCT machine, with a larger range of respiration. It was also found that we can generate the best quality extra-phase image by using the maximum inhalation phase (T0) and maximum exhalation phase (T50) images for extrapolation. Conclusion: In the present study, a method to construct extra-phase images that represent expanded respiratory motion of the patient has been proposed and tested. The movement of organs from a larger respiration amplitude can be predicted by the proposed method. We believe the method may be utilized for realistic simulation of radiation therapy.

• Journal of Broadcast Engineering
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• v.26 no.3
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• pp.258-268
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• 2021

Point cloud content is immersive content that represents real-world objects with three-dimensional (3D) points. In the process of acquiring point cloud data or encoding and decoding point cloud data, the resolution of point cloud content could be degraded. In this paper, we propose a method of progressively enhancing the resolution of sequential point cloud contents through inter-frame registration. To register a point cloud, the iterative closest point (ICP) algorithm is commonly used. Existing ICP algorithms can transform rigid bodies, but there is a disadvantage that transformation is not possible for non-rigid bodies having motion vectors in different directions locally, such as point cloud content. We overcome the limitations of the existing ICP-based method by registering regions with motion vectors in different directions locally between the point cloud content of the current frame and the previous frame. In this manner, the resolution of the point cloud content with geometric movement is enhanced through the process of registering points between frames. We provide four different point cloud content that has been enhanced with our method in the experiment.

• Progress in Medical Physics
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• v.32 no.4
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• pp.172-178
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• 2021

Purpose: This study aimed to develop a deep learning architecture combining two task models to generate synthetic computed tomography (sCT) images from low-tesla magnetic resonance (MR) images to improve metallic marker visibility. Methods: Twenty-three patients with cervical cancer treated with intracavitary radiotherapy (ICR) were retrospectively enrolled, and images were acquired using both a computed tomography (CT) scanner and a low-tesla MR machine. The CT images were aligned to the corresponding MR images using a deformable registration, and the metallic dummy source markers were delineated using threshold-based segmentation followed by manual modification. The deformed CT (dCT), MR, and segmentation mask pairs were used for training and testing. The sCT generation model has a cascaded three-dimensional (3D) U-Net-based architecture that converts MR images to CT images and segments the metallic marker. The performance of the model was evaluated with intensity-based comparison metrics. Results: The proposed model with segmentation loss outperformed the 3D U-Net in terms of errors between the sCT and dCT. The structural similarity score difference was not significant. Conclusions: Our study shows the two-task-based deep learning models for generating the sCT images using low-tesla MR images for 3D ICR. This approach will be useful to the MR-only workflow in high-dose-rate brachytherapy.

• Journal of radiological science and technology
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• v.40 no.1
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• pp.57-62
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• 2017

The purpose of this study is to reconstruct the treatment plan by applying CBCT and DIR to dose changes according to the change of the patient's motion and breast shape in the large breast cancer patients and to compare the doses using TWF, FIF and IMRT. CT and CBCT were performed with MIM6 to create DIRCT and each treatment plan was made. The patient underwent computed tomography simulation in both prone and supine position. The homogeneity index (HI), conformity index (CI), coverage index (CVI) to the left breast as planning target volume (PTV) were determined and the doses to the lung, heart, and right breast as organ at risk (OAR) were compared by using dose-volume histogram and the unique property of each organ. The value of HI of the PTV breast increased in all treatment planning methods using DIRCT, and CVI and CI were decreased in the treatment planning methods using DIRCT.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.1
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• pp.319-323
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• 2012

Objective: To explore the feasibility of shrinking field technique after 40 Gy radiation through 18F-FDG PET/CT during treatment for patients with stage III non-small cell lung cancer (NSCLC). Methods: In 66 consecutive patients with local-advanced NSCLC, 18F-FDG PET/CT scanning was performed prior to treatment and repeated after 40 Gy. Conventionally fractionated IMRT or CRT plans to a median total dose of 66Gy (range, 60-78Gy) were generated. The target volumes were delineated in composite images of CT and PET. Plan 1 was designed for 40 Gy to the initial planning target volume (PTV) with a subsequent 20-28 Gy-boost to the shrunken PTV. Plan 2 was delivering the same dose to the initial PTV without shrinking field. Accumulated doses of normal tissues were calculated using deformable image registration during the treatment course. Results: The median GTV and PTV reduction were 35% and 30% after 40 Gy treatment. Target volume reduction was correlated with chemotherapy and sex. In plan 2, delivering the same dose to the initial PTV could have only been achieved in 10 (15.2%) patients. Significant differences (p<0.05) were observed regarding doses to the lung, spinal cord, esophagus and heart. Conclusions: Radiotherapy adaptive to tumor shrinkage determined by repeated 18F-FDG PET/CT after 40 Gy during treatment course might be feasible to spare more normal tissues, and has the potential to allow dose escalation and increased local control.

• The KIPS Transactions:PartB
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• v.17B no.5
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• pp.355-362
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• 2010

Face tracking is to estimate the motion of a non-rigid face together with a rigid head in 3D, and plays important roles in higher levels such as face/facial expression/emotion recognition. In this paper, we propose an AAM-based face tracking algorithm. AAM has been widely used to segment and track deformable objects, but there are still many difficulties. Particularly, it often tends to diverge or converge into local minima when a target object is self-occluded, partially or completely occluded. To address this problem, we utilize the scale invariant feature transform (SIFT). SIFT is an effective method for self and partial occlusion because it is able to find correspondence between feature points under partial loss. And it enables an AAM to continue to track without re-initialization in complete occlusions thanks to the good performance of global matching. We also register and use the SIFT features extracted from multi-view face images during tracking to effectively track a face across large pose changes. Our proposed algorithm is validated by comparing other algorithms under the above 3 kinds of occlusions.

• The Journal of Korean Society for Radiation Therapy
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• v.30 no.1_2
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• pp.177-183
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• 2018

Purpose : Volumetric Modulated Arc Therapy(VMAT) has the advantage of uniformly and precisely irradiating the tumor to the shape of the tumor while reducing the risk of radiation damage to normal tissues. such as brain cancer, head and neck cancer and prostate cancer, It is being used for treatment. The purpose of this study is to evaluate the usefulness of the Jaw-Tracking technique(JTT) in VMAT for brain and head and neck cancer. Materials and Methods : We selected eight patients with brain and head and neck cancer(4 Brain, 4 head and neck) who were treated with the VMAT treatment technique. Contouring information of the patient's tumor and normal organ was fused to the Rando phantom using the deformable registration of Velocity(Varian, USA). A treatment plan was developed using the Varian Eclipse(ver 15.5, Varian, USA) with the same patient actual beam parameters except for the use of jaw-tracking. As the evaluation index, the maximum dose and mean dose of target and OAR were compared and a portal dosimetry was performed for the treatment plan verification. Results : When using JTT, the relative dose of OAR decreased by 5.24 % and the maximum dose by 7.05 %, respectively, compared with the Static-Jaw technique(SJT). In the various OARs, the mean dose and maximum dose reduction ranges ranged from 0.01 to 3.16 Gy and from 0.12 to 6.27 Gy, respectively. In the case of the target, the maximum dose of GTV, CTV, PTV decreased by 0.17 %, 0.43 %, and 0.37 % in JTT, and the mean dose decreased by 0.24 %, 0.47 % and 0.47 %, respectively. Gamma analysis The JTT and SJT passing rates were $98{\pm}1.73%$ and $97{\pm}1.83%$ on the basis of 3 % / 3 mm, respectively. Comparing the doses of all OARs applied to the experiment, it was found that the use of JTT resulted in a significant decrease in dose due to additional jaw shielding besides MLC than SJT. Conclusion : In radiation therapy using VMAT treatment plan, we can apply JTT in the case of adjacent tumor and normal organs such as brain cancer and head and neck cancer, and in radiotherapy required large field and high energy caused increase leakage dose through MLC. It is considered that the target dose of PTV can be increased by lowering the dose of normal tissue surrounding the tumor.