[Retrospective study on the modified Uhl technique of closed reduction and percutaneous pin in the treatment of Colles' fracture].

Objective: To retrospectively assess the advantages of the modified Uhl technique in the treatment of Colles' fracture guided by the principles of Chinese osteosynthesis (CO) concept.

Methods: A retrospective study was conducted on 358 patients with Colles' fracture treated with the modified Uhl technique of closed reduction and percutaneous pin between January 2016 and June 2021. Out of these, 120 eligible cases were selected and categorized into two groups according to different surgical methods:the closed reduction and percutaneous pin group, and the open reduction group.

Monocular Image-Based 3-D Model Retrieval: A Benchmark.

Monocular image-based 3-D model retrieval aims to search for relevant 3-D models from a dataset given one RGB image captured in the real world, which can significantly benefit several applications, such as self-service checkout, online shopping, etc. To help advance this promising yet challenging research topic, we built a novel dataset and organized the first international contest for monocular image-based 3-D model retrieval. Moreover, we conduct a thorough analysis of the state-of-the-art methods.

Deep Correlated Joint Network for 2-D Image-Based 3-D Model Retrieval.

In this article, we propose a novel deep correlated joint network (DCJN) approach for 2-D image-based 3-D model retrieval. First, the proposed method can jointly learn two distinct deep neural networks, which are trained for individual modalities to learn two deep nonlinear transformations for visual feature extraction from the co-embedding feature space. Second, we propose the global loss function for the DCJN, consisting of a discriminative loss and a correlation loss.

Sequential Saliency Guided Deep Neural Network for Joint Mitosis Identification and Localization in Time-Lapse Phase Contrast Microscopy Images.

The analysis of cell mitotic behavior plays important role in many biomedical research and medical diagnostic applications. To improve the accuracy of mitosis detection in automated analysis systems, this paper proposes the sequential saliency guided deep neural network (SSG-DNN) to jointly identify and localize mitotic events in time-lapse phase contrast microscopy images. It consists of three key modules.

Multi-Domain & Multi-Task Learning for Human Action Recognition.

Domain-invariant (view-invariant & modalityinvariant) feature representation is essential for human action recognition. Moreover, given a discriminative visual representation, it is critical to discover the latent correlations among multiple actions in order to facilitate action modeling. To address these problems, we propose a multi-domain & multi-task learning (MDMTL) method to (1) extract domain-invariant information for multi-view and multi-modal action representation and (2) explore the relatedness among multiple action categories.

View-Based 3-D Model Retrieval: A Benchmark.

View-based 3-D model retrieval is one of the most important techniques in numerous applications of computer vision. While many methods have been proposed in recent years, to the best of our knowledge, there is no benchmark to evaluate the state-of-the-art methods. To tackle this problem, we systematically investigate and evaluate the related methods by: 1) proposing a clique graph-based method and 2) reimplementing six representative methods.

Benchmarking a Multimodal and Multiview and Interactive Dataset for Human Action Recognition.

Human action recognition is an active research area in both computer vision and machine learning communities. In the past decades, the machine learning problem has evolved from conventional single-view learning problem, to cross-view learning, cross-domain learning and multitask learning, where a large number of algorithms have been proposed in the literature. Despite having large number of action recognition datasets, most of them are designed for a subset of the four learning problems, where the comparisons between algorithms can further limited by variances within datasets, experimental configurations, and other factors.

Multi-Modal Clique-Graph Matching for View-Based 3D Model Retrieval.

Multi-view matching is an important but a challenging task in view-based 3D model retrieval. To address this challenge, we propose an original multi-modal clique graph (MCG) matching method in this paper. We systematically present a method for MCG generation that is composed of cliques, which consist of neighbor nodes in multi-modal feature space and hyper-edges that link pairwise cliques.

Hierarchical Clustering Multi-Task Learning for Joint Human Action Grouping and Recognition.

This paper proposes a hierarchical clustering multi-task learning (HC-MTL) method for joint human action grouping and recognition. Specifically, we formulate the objective function into the group-wise least square loss regularized by low rank and sparsity with respect to two latent variables, model parameters and grouping information, for joint optimization. To handle this non-convex optimization, we decompose it into two sub-tasks, multi-task learning and task relatedness discovery.

Jointly Learning Multiple Sequential Dynamics for Human Action Recognition.

Discovering visual dynamics during human actions is a challenging task for human action recognition. To deal with this problem, we theoretically propose the multi-task conditional random fields model and explore its application on human action recognition. For visual representation, we propose the part-induced spatiotemporal action unit sequence to represent each action sample with multiple partwise sequential feature subspaces.

[Comparison between mini-traumatic bone-grafting and non-bone-grafting in percutaneous K-wire fixation to treat the calcaneal fractures].

Objective: To compare the effect between mini-traumatic bone-grafting and non-bone-grafting in percutaneous K-wire fixation for treating the calcaneal fractures.

Methods: From 2002 to 2006, 112 patients with the type II (Paley type) fractures of calcaneus were studied. There were 56 cases in bone-grafting group involving 36 males and 20 famales,aged from 21 to 65, averaged (42.