Speed and precision are important for object detection algorithms. In this paper, a novel object detection algorithm based on color histogram and adaptive bandwidth mean shift is proposed. The algorithm is capable of detecting objects rapidly and precisely. It is composed of two stages: a rough detection stage and a precise detection stage. At the rough detection stage, histogram back projection and thresholding are applied to fast object identification and rough global localization. At the precise detection stage, the precise position, size and orientation are derived under the adaptive bandwidth mean shift framework. Experiments verify that the algorithm is able to detect the size, position and orientation of general objects rapidly and precisely.

To facilitate training of endodontic operations, we have developed an interactive virtual environment to simulate endodontic shaping operations. This paper presents methodologies for dynamic modeling, visual/haptic display and model validation of endodontic shaping. We first investigate the forces generated in the course of shaping operations and discuss the challenging issues in their modeling. Based on the special properties and constraints associated with both pulpal tissue and endodontic files, we propose a dynamic model to simulate endodontic shaping, which is a smoothed particle based model derived for the pulpal tissue coupled with a finite element model for the endodontic files. The virtual environment has been implemented with both graphic and haptic interfaces. Furthermore, the effectiveness of the proposed model has been validated by experimental results through a novel robotic endodontic measurement system.

In the above titled paper (ibid., vol. 23, no. 3, pp. 443-458, Jun 07), Fig. 11 was printed with some mathematical symbols missing in lines 3, 6, 8, and 13. The corrected figure and its caption are presented here.

To facilitate training of endodontic operations, we have developed an interactive virtual environment to simulate endodontic shaping. This paper presents methodologies for haptic modeling, display and validation of endodontic shaping. We first investigate the forces generated in the course of shaping operations and discuss the challenging issues in their modeling. Based on the special properties and constraints associated with both pulpal tissue and endodontic files, we propose a haptic model to simulate endodontic shaping operations, which is a smoothed particle based dynamic model derived for the pulpal tissue coupled with a finite element model for the endodontic files. Furthermore, the effectiveness of the proposed model has been validated by experimental results through a novel robotic endodontic measurement system

Accurate estimation of interaction forces for endodontic shaping is fundamental to the interactive simulation of this operation. By applying new statistical learning techniques to this problem, this paper proposes a novel estimation method to acquire an optimized interaction force model to characterize input-output force mapping for endodontic shaping. We first present a novel robotic measurement system to acquire interaction forces in endodontic shaping and establish the needed training set. Then we propose a support vector regression model to learn the input-output force mapping for endodontic shaping. The regression model uses RBF kernel for training, and the optimized parameters of which are obtained by experiments. The learned model can convincingly estimate the interaction force resulting from endodontic shaping. And the effectiveness of the model has been evaluated by error measurement results

Effective and efficient simulation of tissue-tool interactions is the key to a virtual endodontic training system. This paper presents a new force model for effectively simulating the interactions of the pulpal tissue with the endodontic tools. Based on the smoothed particle hydrodynamics (SPH) method, a particle-based pulpal tissue model is proposed, which takes into account characteristics of the tissue and constraints associated with both the tissue and current haptic devices. The stability, accuracy and speed of the proposed model are guaranteed by applying suitable smoothing kernels to calculate different forces applied to the pulpal tissue. Furthermore, a finite element model is used to model the deformation and dynamics of the endodontic tools. We also derive several boundary constraints associated with interactions of the pulpal tissue with the endodontic tools. With this force model, the virtual system can provide the convincing sense of touch of endodontic procedures in real time using current high fidelity haptic devices.

Endodontic treatment is one of the most common dental procedures employed in modern dentistry. Although there have been many works in medical simulation in the past two decades, little research has been done on modeling and simulation of endodontic procedures. This work presents a methodology to design and implement a virtual endodontics test bed for facilitating surgical training of root canal skills. In order to make the system more efficient and effective, the work focuses on the simulation of the most critical step in the entire endodontic procedure, i.e. shaping and cleaning. The paper first proposes a novel approach for estimating filing force and torque by developing a measurement system. Then, a hybrid modeling scheme for endodontic simulation is presented, which consists of a geometric-based endodontic instrument model, a physically-based root canal model, and a parameter identification method for the model.