scholarly journals MR and CT Image Fusion Using Nonlinear Anisotropic Filtering in PCA Domain

2021 ◽  
Vol 1964 (6) ◽  
pp. 062058
Author(s):  
S Rama Kishore Reddy ◽  
V Swathi ◽  
K Anusha
2015 ◽  
Vol 54 (06) ◽  
pp. 247-254 ◽  
Author(s):  
A. Kapfhammer ◽  
T. Winkens ◽  
T. Lesser ◽  
A. Reissig ◽  
M. Steinert ◽  
...  

SummaryAim: To retrospectively evaluate the feasibility and value of CT-CT image fusion to assess the shift of peripheral lung cancers with/-out chest wall infiltration, comparing computed tomography acquisitions in shallow-breathing (SB-CT) and deep-inspiration breath-hold (DIBH-CT) in patients undergoing FDG-PET/ CT for lung cancer staging. Methods: Image fusion of SB-CT and DIBH-CT was performed with a multimodal workstation used for nuclear medicine fusion imaging. The distance of intrathoracic landmarks and the positional shift of tumours were measured using semitransparent overlay of both CT series. Statistical analyses were adjusted for confounders of tumour infiltration. Cutoff levels were calculated for prediction of no-/infiltration. Results: Lateral pleural recessus and diaphragm showed the largest respiratory excursions. Infiltrating lung cancers showed more limited respiratory shifts than non-infiltrating tumours. A large respiratory tumour-motility accurately predicted non-infiltration. However, the tumour shifts were limited and variable, limiting the accuracy of prediction. Conclusion: This pilot fusion study proved feasible and allowed a simple analysis of the respiratory shifts of peripheral lung tumours using CT-CT image fusion in a PET/CT setting. The calculated cutoffs were useful in predicting the exclusion of chest wall infiltration but did not accurately predict tumour infiltration. This method can provide additional qualitative information in patients with lung cancers with contact to the chest wall but unclear CT evidence of infiltration undergoing PET/CT without the need of additional investigations. Considering the small sample size investigated, further studies are necessary to verify the obtained results.


2019 ◽  
Vol 14 (7) ◽  
pp. 658-666
Author(s):  
Kai-jian Xia ◽  
Jian-qiang Wang ◽  
Jian Cai

Background: Lung cancer is one of the common malignant tumors. The successful diagnosis of lung cancer depends on the accuracy of the image obtained from medical imaging modalities. Objective: The fusion of CT and PET is combining the complimentary and redundant information both images and can increase the ease of perception. Since the existing fusion method sare not perfect enough, and the fusion effect remains to be improved, the paper proposes a novel method called adaptive PET/CT fusion for lung cancer in Piella framework. Methods: This algorithm firstly adopted the DTCWT to decompose the PET and CT images into different components, respectively. In accordance with the characteristics of low-frequency and high-frequency components and the features of PET and CT image, 5 membership functions are used as a combination method so as to determine the fusion weight for low-frequency components. In order to fuse different high-frequency components, we select the energy difference of decomposition coefficients as the match measure, and the local energy as the activity measure; in addition, the decision factor is also determined for the high-frequency components. Results: The proposed method is compared with some of the pixel-level spatial domain image fusion algorithms. The experimental results show that our proposed algorithm is feasible and effective. Conclusion: Our proposed algorithm can better retain and protrude the lesions edge information and the texture information of lesions in the image fusion.


2006 ◽  
Vol 92 (2) ◽  
pp. 118-123 ◽  
Author(s):  
Raffaella Cambria ◽  
Federica Cattani ◽  
Mario Ciocca ◽  
Cristina Garibaldi ◽  
Giampiero Tosi ◽  
...  

Aims and Background The importance of optimal daily patient positioning has been stressed in order to ensure treatment reproducibility and gain in accuracy and precision. We report our data on the 3D setup uncertainty during radiation therapy for prostate cancer using the CT image fusion technique. Methods Ten consecutive patients scheduled for radiation therapy for prostate cancer underwent 5 prone position CT scans using an individualized immobilization cast. These different setups were analyzed using the image fusion module of the ERGO 3D-Line Medical System (Milan, Italy) treatment planning system. The isocenter and the body marker displacements were measured. Results The 3D isocenter dislocations were quantified: systematic error was Σ3D = 3.9 mm, whereas random error was σ3D = 1 mm. The mean of the minimum displacements was 0.2 ± 1 mm showing that the immobilization device used allows an accurate setup to be obtained. Single direction errors were also measured showing systematic errors, ΣAP = 2.6 mm, ΣLL = 0.6 mm, ΣSI = 3 mm in the anterior-posterior, latero-lateral, superior-inferior direction, respectively. Related random errors were σAP = 1 mm, σLL = 0.6 mm, σSI = 1.2 mm. In terms of accuracy, our uncertainties are similar to those reported in the literature. Conclusions By applying the CT image fusion technique, a 3D study on setup accuracy was performed. We demonstrated that the use of an individualized immobilization system for prostate treatment is adequate to obtain good setup accuracy, as long as a high-quality positioning control method, such as the stereoscopic X-ray-based positioning system, is used.


2015 ◽  
Vol 22 (3) ◽  
pp. 217-222 ◽  
Author(s):  
Michele Diana ◽  
Peter Halvax ◽  
Damien Mertz ◽  
Andras Legner ◽  
Jean-Marcel Brulé ◽  
...  
Keyword(s):  

2022 ◽  
Vol 71 ◽  
pp. 103096
Author(s):  
Leiner Barba-J ◽  
Lorena Vargas-Quintero ◽  
Jose A. Calderón-Agudelo

2010 ◽  
Vol 07 (02) ◽  
pp. 99-107 ◽  
Author(s):  
NEMIR AL-AZZAWI ◽  
WAN AHMED K. WAN ABDULLAH

Medical image fusion has been used to derive useful information from multimodality medical image data. This paper presents a dual-tree complex contourlet transform (DT-CCT) based approach for the fusion of magnetic resonance image (MRI) and computed tomography (CT) image. The objective of the fusion of an MRI and a CT image of the same organ is to obtain a single image containing as much information as possible about that organ for diagnosis. The limitation of directional information of dual-tree complex wavelet (DT-CWT) is rectified in DT-CCT by incorporating directional filter banks (DFB) into the DT-CWT. To improve the fused image quality, we propose a new method for fusion rules based on the principle component analysis (PCA) which depend on frequency component of DT-CCT coefficients (contourlet domain). For low frequency coefficients, PCA method is adopted and for high frequency coefficients, the salient features are picked up based on local energy. The final fusion image is obtained by directly applying inverse dual tree complex contourlet transform (IDT-CCT) to the fused low and high frequency coefficients. The DT-CCT produces images with improved contours and textures, while the property of shift invariance is retained. The experimental results showed that the proposed method produces fixed image with extensive features on multimodality.


2017 ◽  
Vol 34 (3) ◽  
pp. e2933 ◽  
Author(s):  
Ayan Seal ◽  
Debotosh Bhattacharjee ◽  
Mita Nasipuri ◽  
Dionisio Rodríguez-Esparragón ◽  
Ernestina Menasalvas ◽  
...  

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