3D/2D Vessel Registration Based on Monte Carlo Tree Search and Manifold Regularization.

The augmented intra-operative real-time imaging in vascular interventional surgery, which is generally performed by projecting preoperative computed tomography angiography images onto intraoperative digital subtraction angiography (DSA) images, can compensate for the deficiencies of DSA-based navigation, such as lack of depth information and excessive use of toxic contrast agents. 3D/2D vessel registration is the critical step in image augmentation. A 3D/2D registration method based on vessel graph matching is proposed in this study. For rigid registration, the matching of vessel graphs can be decomposed into continuous states, thus 3D/2D vascular registration is formulated as a search tree problem. The Monte Carlo tree search method is applied to find the optimal vessel matching associated with the highest rigid registration score. For nonrigid registration, we propose a novel vessel deformation model based on manifold regularization. This model incorporates the smoothness constraint of vessel topology into the objective function. Furthermore, we derive simplified gradient formulas that enable fast registration. The proposed technique undergoes evaluation against seven rigid and three nonrigid methods using a variety of data - simulated, algorithmically generated, and manually annotated - across three vascular anatomies: the hepatic artery, coronary artery, and aorta. Our findings show the proposed method's resistance to pose variations, noise, and deformations, outperforming existing methods in terms of registration accuracy and computational efficiency. The proposed method demonstrates average registration errors of 2.14 mm and 0.34 mm for rigid and nonrigid registration, and an average computation time of 0.51 s.

Sparse deformation prediction using Markove Decision Processes (MDP) for Non-rigid registration of MR image.

BACKGROUND AND OBJECTIVE: A framework of sparse deformation prediction using Markove Decision Processes is proposed for achieving a rapid and accurate registration by providing a suitable initial deformation. METHODS: In the proposed framework, the tree is built based on the training set for each patch from the template image. The template patch is considered as the root. The node is the patch group in which multiple similar patches are extracted around a key point on the training image. Given the linkages between patch groups in the tree, MDP is introduced to select the optimal path with highest registration accuracy from each training patch to the template patch. The deformation between them is estimated along the selected path by patch-wise registration which can be realized by a non-learning-based method. Given the patches on a testing image, their best matching patches are fast chosen from the training patches and the corresponding deformations constitute a sparse deformation. A dense deformation for the entire test image is subsequently interpolated and used as an initial deformation for further registration. RESULTS: With the non-learning-based registration as the baseline method, the proposed framework is evaluated using three datasets of inter-subject brain MR images with three learning-based methods. Experimental results of the non-learning-based method using the proposed framework reveal that the computation time is reduced by fivefold after using the proposed framework. And, with the same baseline method, the proposed framework demonstrates the higher accuracy than three learning-based methods which predicts the initial deformation at image scale. The mean Dice of three datasets for the tissues of the brain are 73.52%, 70.73% and 64.82%, respectively. CONCLUSIONS: The proposed framework rapidly registers the inter-subject brains and achieves the high mean Dice for the tissues of the brain.

Evidence-based assessment of ADHD diagnosis in children and adolescents.

This study illustrates the accuracy and efficiency of using an evidence-based assessment (EBA) strategy for diagnosis of attention-deficit/hyperactivity disorder (ADHD) by integrating the scale scores obtained on BASC-3 teacher and parent rating scales. The examined process used empirical diagnostic likelihood ratios (DLRs) derived from a sample of children with ADHD (N = 339) matched on demographic characteristics from the normative sample. The results show that behavioral scales of executive functioning and functional communication provided incremental utility in ADHD diagnosis. With a revised probability of .80 or higher as the diagnostic criterion, teachers, and parents positively diagnosed 70% and 94% of the ADHD cases respectively. The EBA approach was efficient, with four scales on average used to reach the proposed posterior probability for final diagnosis. Finally, teachers and parents demonstrated a high agreement with respect to the diagnosis results and scales used for the diagnosis.

Family economic hardship and Chinese adolescents' sleep quality: A moderated mediation model involving perceived economic discrimination and coping strategy.

The association between family economic hardship and adolescent adjustment outcomes, including sleep quality, is well-established. Few studies, however, have examined the mediating and moderating mechanisms underlying the relation between family economic hardship and adolescents' sleep quality. The aim of this study was to investigate the effect of family economic hardship on Chinese adolescents' sleep quality, as well as the role of perceived economic discrimination as a mediator and the role of coping strategy as a moderator. Survey data from a cross-sectional sample of 997 Chinese adolescents (45% male, mean age = 15.04 years) were analyzed using path analysis in Mplus 7.0. The results of this study indicated that family economic hardship was significantly associated with adolescents' sleep quality. This association was mediated by adolescents' perceived economic discrimination. In addition, adolescents' coping strategy significantly moderated the path from perceived economic discrimination to sleep quality, with the "shift" coping strategy as a protective factor. The present study contributes to our understanding of key mechanisms underlying the association between family economic hardship and adolescent sleep quality and highlights the importance of improving sleep quality for adolescents exposed to economic hardship.