Preparing the books to read every day is enjoyable for many people. However, there are still many people who also don't like reading. This is a problem. But, when you can support others to start reading, it will be better. One of the books that can be recommended for new readers is experience and education. This book is not kind of difficult book to read. It can be read and understand by the new readers.

Experience and Education.

物件導向軟體之架構(Object-Oriented Software Construction)探討

The culture of education

https://www.cs.ucla.edu/~dt/papers/mia96/mia96.pdf

Deformable models in medical image analysis: a survey

Simulation is a technique-not a technology-to replace or amplify real experiences with guided experiences that evoke or replicate substantial aspects of the real world in a fully interactive manner. The diverse applications of simulation in health care can be categorised by 11 dimensions: aims and purposes of the simulation activity; unit of participation; experience level of participants; health care domain; professional discipline of participants; type of knowledge, skill, attitudes, or behaviours addressed; the simulated patient's age; technology applicable or required; site of simulation; extent of direct participation; and method of feedback used. Using simulation to improve safety will require full integration of its applications into the routine structures and practices of health care. The costs and benefits of simulation are difficult to determine, especially for the most challenging applications, where long term use may be required. Various driving forces and implementation mechanisms can be expected to propel simulation forward, including professional societies, liability insurers, health care payers, and ultimately the public. The future of simulation in health care depends on the commitment and ingenuity of the health care simulation community to see that improved patient safety using this tool becomes a reality.

https://qualitysafety.bmj.com/content/qhc/13/suppl_1/i2.full.pdf

The future vision of simulation in health care

Non-linear models used in dynamic simulations usually require the solution of multiple large and sparse linear systems in a successive manner. In this paper, we conduct a study of numerical solvers in the framework of real-time soft tissue deformation. Domain Decomposition paradigm has the potential of providing parallelism at both levels of equation assembling and linear system solving. In our case domain decomposition is employed to solve a non-linear model in a dynamic simulation in order to meet real-time computation by using parallel architecture. Numerical test on liver deformations using a non-linear deformation model is presented to evaluate the acceleration impact of the domain decomposition paradigm. Performances tests clearly show the efficiency of using a domain decomposition approach for real-time feedback.

https://hal.archives-ouvertes.fr/hal-02400982/document

Simulation of soft tissue deformation in real-time using domain decomposition

We present a data-assimilation Bayesian framework in the context of laser ablation for the treatment of cancer. For solving the nonlinear estimation of the tissue temperature evolving during the therapy, the Unscented Kalman Filter (UKF) predicts the next thermal status and controls the ablation process, based on sparse temperature information. The purpose of this paper is to study the outcome of the prediction model based on UKF and to assess the influence of different model settings on the framework performances. In particular, we analyze the effects of the time resolution of the filter and the number and the location of the observations. Clinical Relevance - The application of a data-assimilation approach based on limited temperature information allows to monitor and predict in real-time the thermal effects induced by thermal therapy for tumors.

Unscented Kalman Filtering for Real Time Thermometry During Laser Ablation Interventions

Image-guided hepatic surgery is progressively becoming a standard for certain interventions. However, limited dose radiation requirements result in lower quality images, making it difficult to localize tumors and other structures of interest. In this paper we propose an automatic registration method exploiting the matching of the vascular trees, visible in both pre and intra-operative images. The graphs are automatically matched using an algorithm combining a Gaussian Process Regression and biomechanical model. This process is automatic, does not require any initialization and handles large intra-operative deformations.

https://hal.archives-ouvertes.fr/hal-01587952/document

Automatic biomechanical graph matching CT-CBCT fusion

The Discrete Exterior Calculus (DEC), a new method for solving fluid dynamics problems in a computationally efficient way is introduced. It deals with the vorticity-based equations, and updates the vorticity by a backtracking step, which makes the computation circulation-preserving at a discrete level, as well as stable. The pre-computation of operators and the use of larger time steps result in fast simulations. We illustrate this method by simulating a coil embolization procedure used for the treatment of cerebral aneurysms. This complex medical procedure requires careful planning and advanced technical skills in order to be successful. Using the DEC method, the complex blood flow patterns within the aneurysm are computed, and the two-fold interaction between coils and blood is also considered. This approach allows for fast computation of coil-flow bilateral influence, resulting in interactive simulations that can be used for advanced training of interventional radiology procedures.

/pdf/interactive-blood-coil-simulation-using-discrete-exterior-go9skqhsrn.pdf

Interactive Blood-Coil Simulation using Discrete Exterior Calculus

Purpose: The purpose of this paper is to present a method for real-time 2D-3D non-rigid registration using a single fluoroscopic image. Such a method can find applications in surgery, interventional radiology and radiotherapy. By estimating a three-dimensional displacement field from a 2D X-ray image, anatomical structures segmented in the preoperative scan can be projected onto the 2D image, thus providing a mixed reality view. Methods: A dataset composed of displacement fields and 2D projections of the anatomy is generated from the preoperative scan. From this dataset, a neural network is trained to recover the unknown 3D displacement field from a single projection image. Results: Our method is validated on lung 4D CT data at different stages of the lung deformation. The training is performed on a 3D CT using random (non domain-specific) diffeomorphic deformations, to which perturbations mimicking the pose uncertainty are added. The model achieves a mean TRE over a series of landmarks ranging from 2.3 to 5.5 mm depending on the amplitude of deformation. Conclusion: In this paper, a CNN-based method for real-time 2D-3D non-rigid registration is presented. This method is able to cope with pose estimation uncertainties, making it applicable to actual clinical scenarios, such as lung surgery, where the C-arm pose is planned before the intervention.

Stéphane Cotin

Papers

Simulation of soft tissue deformation in real-time using domain decomposition

Unscented Kalman Filtering for Real Time Thermometry During Laser Ablation Interventions

Automatic biomechanical graph matching CT-CBCT fusion

Interactive Blood-Coil Simulation using Discrete Exterior Calculus

CNN-based real-time 2D-3D deformable registration from a single X-ray projection