Locally Adaptive Total p-Variation Regularization for Non-Rigid Image Registration With Sliding Motion

Gong, Lun; Duan, Luwen; Dai, Yakang; He, Qi; Zuo, Siyang; Fu, Tianxiao; Yang, Xiaodong; Zheng, Jian

doi:10.1109/tbme.2020.2964695

Cited by 11 publications

(7 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In 2019, to restore the ideal deformation field between chest images containing sliding and smooth motion patterns, L. Gong et al [ 78 ] proposed a regularization term called locally adaptive total P-variation (LaTpV) and embedded it into a parametric registration framework to accurately restore lung motion. LaTpV adaptively balances the smoothness and discontinuity of the displacement field, is suitable for sliding motion correction, and has potential clinical application in the adjustment of radiotherapy schedule.…”

Section: Resultsmentioning

confidence: 99%

Current Research Status of Respiratory Motion for Thorax and Abdominal Treatment: A Systematic Review

Wu,

Wang,

Chu

et al. 2024

Biomimetics

View full text Add to dashboard Cite

Malignant tumors have become one of the serious public health problems in human safety and health, among which the chest and abdomen diseases account for the largest proportion. Early diagnosis and treatment can effectively improve the survival rate of patients. However, respiratory motion in the chest and abdomen can lead to uncertainty in the shape, volume, and location of the tumor, making treatment of the chest and abdomen difficult. Therefore, compensation for respiratory motion is very important in clinical treatment. The purpose of this review was to discuss the research and development of respiratory movement monitoring and prediction in thoracic and abdominal surgery, as well as introduce the current research status. The integration of modern respiratory motion compensation technology with advanced sensor detection technology, medical-image-guided therapy, and artificial intelligence technology is discussed and analyzed. The future research direction of intraoperative thoracic and abdominal respiratory motion compensation should be non-invasive, non-contact, use a low dose, and involve intelligent development. The complexity of the surgical environment, the constraints on the accuracy of existing image guidance devices, and the latency of data transmission are all present technical challenges.

show abstract

Section: Resultsmentioning

confidence: 99%

Current Research Status of Respiratory Motion for Thorax and Abdominal Treatment: A Systematic Review

Wu,

Wang,

Chu

et al. 2024

Biomimetics

View full text Add to dashboard Cite

show abstract

“…However, in our calculation process of the dynamic ventilation sequence, the registrations of phases pairs near the EE phase (DIR of T50/T40 and T50/T60) are faced with such a problem, especially due to the following: (a) When undergoing 4DCT scanning, patients tend to hold the breath for a short time at end‐exhalation, which makes the image of T60 phase very similar to that of T50 phase 22 . (b) Compared with common smoothness‐regularized strategy, in the TV algorithm we used, the sliding‐preserving constraint was imposed on the entire DVF, including most non‐sliding regions 39 . This makes it necessary to consider the robustness of input DVFs when selecting the DIR‐based expansion estimation metrics, whereas IJF method, as a proven robust CT ventilation algorithm, 31,32 is a suitable choice for our task.…”

Section: Discussionmentioning

confidence: 99%

“…22 (b) Compared with common smoothnessregularized strategy, in the TV algorithm we used, the sliding-preserving constraint was imposed on the entire DVF, including most non-sliding regions. 39 This makes it necessary to consider the robustness of input DVFs when selecting the DIR-based expansion estimation metrics,whereas IJF method,as a proven robust CT ventilation algorithm, 31,32 is a suitable choice for our task. In further clinical implementations, imaging denoising and artifact correction 40 will be added into the workflow to deal with 4DCT scans with different imaging qualities in actual scenes.…”

Section: Discussionmentioning

confidence: 99%

Volumetric multiphase ventilation imaging based on four‐dimensional computed tomography for functional lung avoidance radiotherapy

et al. 2022

View full text Add to dashboard Cite

Purpose Current computed tomography (CT)‐based lung ventilation imaging (CTVI) techniques derive a static ventilation image without temporal information. This research aims to develop a four‐dimensional CT (4DCT)‐based multiphase dynamic ventilation imaging framework capable of recovering the entire ventilation process throughout the breathing cycle for functional lung avoidance radiotherapy (FLART). Methods A total of 15 free‐breathing thoracic 4DCT scans of lung or esophageal cancer patients were collected from the public datasets. The lung region of each phase image was first delineated, and then the mask‐free isotropic total variation image registration algorithm was used to derive the deformation vector fields between the end‐expiration (EE) phase and other phases. As a surrogate of ventilation, the voxel‐wise local expansion ratio of each phase relative to the EE phase was estimated using the parameterized Integrated Jacobian Formulation method in the EE phase coordinate. Lastly, the dynamic ventilation images were generated by warping these phase‐specific local expansion distributions with a same geometry into their respective breathing phases. Quantitative analysis, including interphase Spearman correlation coefficients, voxel‐wise, and regional‐wise expansion/contraction tracking, were performed to indirectly validate the proposed method. Results The proposed method maintains the physiological meaning of ventilation on each phase and enables to recover the dynamic lung ventilation process. The mean interphase Spearman correlations ranged between 0.23 ± 0.20 and 0.93 ± 0.04 and decreased near the EE phase. Only 26.2% (2.59E + 6 out of 9.89E + 6) of lung voxels exhibited the same expansion/contraction pattern as the global lung. Qualitative and quantitative evaluations of the interphase ventilation distribution difference show that ventilation spatiotemporal heterogeneities generally exist during respiration. Conclusions In contrast to conventional CTVI metrics, our method enables to extract additional phase‐resolved respiration‐correlated information and reflects the generally existed ventilation spatiotemporal heterogeneities. Subsequent studies with quantitative phase‐by‐phase cross‐modality evaluations will further explore its potential to deepen our understanding of lung function and respiration mechanics and also to facilitate more accurate implementation of FLART.

show abstract

“…is form is the earliest proposed by He et al and Lusting et al ey proposed this model on the basis that the MRI images of general organs are segmented and smooth, which means that there is a small total variation, and are also sparse in the wavelet transform domain, so this model is reasonable for MRI reconstruction. Many experiments have also proved that this model is better than using wavelet transform alone or full variation regular term reconstruction [16]. However, since l 1 and TV norms are convex and nonsmooth, it is very difficult to solve this problem.…”

Section: Mri Image Reconstruction Based On Compressed Sensingmentioning

confidence: 97%

Diagnostic Value of Magnetic Resonance Image Feature Analysis under Reconstruction Algorithm for Knee Epiphyseal Injury

Tang

Zhou

et al. 2022

Scientific Programming

View full text Add to dashboard Cite

To analyze the diagnostic value of magnetic resonance imaging (MRI) in epiphyseal injury of adolescent children, MRI images of 26 adolescent knee joint injuries were selected. The image display before and after reconstruction based on the compressed sensing theory (CS) algorithm was compared and analyzed, so did the signal-to-noise ratio of knee MRI reconstructed images under 2D random sampling and radial sampling at different sampling rates. The results showed that the sharpness, specificity, and accuracy of images reconstructed by the CS algorithm were significantly higher than those before reconstruction P < 0.05 . When the sampling rates were almost the same (20%, 40%, and 60%), the signal-to-noise ratio (SNR) of the reconstructed knee MRI images by random sampling was higher than that by radial sampling (about 9%, 6%, and 3% higher, respectively), that is, the information contained by random sampling was larger than that by radial sampling. It overcame the defects of undisplaced epiphyseal injuries in children and adolescents that cannot be found by plain X-ray films and can clearly and accurately diagnose epiphyseal injuries and fracture types that cannot be seen by plain X-ray films. To sum up, the MRI image reconstruction algorithm based on compressed sensing theory can effectively improve the diagnosis effect of knee epiphyseal injury.

show abstract

Locally Adaptive Total p-Variation Regularization for Non-Rigid Image Registration With Sliding Motion

Cited by 11 publications

References 41 publications

Current Research Status of Respiratory Motion for Thorax and Abdominal Treatment: A Systematic Review

Current Research Status of Respiratory Motion for Thorax and Abdominal Treatment: A Systematic Review

Volumetric multiphase ventilation imaging based on four‐dimensional computed tomography for functional lung avoidance radiotherapy

Diagnostic Value of Magnetic Resonance Image Feature Analysis under Reconstruction Algorithm for Knee Epiphyseal Injury

Contact Info

Product

Resources

About