62 research outputs found
Dense Deformation Field Estimation for Atlas Registration using the Active Contour Framework
In this paper, we propose a new paradigm to carry outthe registration task with a dense deformation fieldderived from the optical flow model and the activecontour method. The proposed framework merges differenttasks such as segmentation, regularization, incorporationof prior knowledge and registration into a singleframework. The active contour model is at the core of ourframework even if it is used in a different way than thestandard approaches. Indeed, active contours are awell-known technique for image segmentation. Thistechnique consists in finding the curve which minimizesan energy functional designed to be minimal when thecurve has reached the object contours. That way, we getaccurate and smooth segmentation results. So far, theactive contour model has been used to segment objectslying in images from boundary-based, region-based orshape-based information. Our registration technique willprofit of all these families of active contours todetermine a dense deformation field defined on the wholeimage. A well-suited application of our model is theatlas registration in medical imaging which consists inautomatically delineating anatomical structures. Wepresent results on 2D synthetic images to show theperformances of our non rigid deformation field based ona natural registration term. We also present registrationresults on real 3D medical data with a large spaceoccupying tumor substantially deforming surroundingstructures, which constitutes a high challenging problem
Atlas-based segmentation of medical images locally constrained by level sets
Atlas-based segmentation has become a standard paradigm for exploiting prior knowledge in medical image segmentation. In this paper, we propose a method to exploit both the robustness of global registration techniques and the accuracy of a local registration based on level set tracking. First, the atlas is globally put in correspondence with the patient image by an affine and an intensity-based non rigid registration. Based on this rough initialisation, the level set functions corresponding to particular objects of interest of the deformed atlas are used to segment the corresponding objects in the patient image. We propose a technique to derive a dense deformation field from the motion of these level set functions. This is particularly important when we want to infer the position of invisible structures like the brain sub-thalamic nuclei from the position of visible surrounding structures. This can also be advantageously exploited to register an atlas following a hierarchical approach. Results are shown on 2D synthetic images and 2D real images extracted from brain and prostate MR volumes and neck CT volumes
Relative Anatomical Location for Statistical Non-Parametric Brain Tissue Classification in MR Images
An Active Contour-based Atlas Registration Model for Automatic Subthalamic Nucleus Targeting on MRI: Method and Validation
This paper presents a new non parametric atlas registration framework, derived from the optical flow model and the active contour theory, applied to automatic subthalamic nucleus (STN) targeting in deep brain stimulation (DBS) surgery. In a previous work, we demonstrated that the STN position can be predicted based on the position of surrounding visible structures, namely the lateral and third ventricles. A STN targeting process can thus be obtained by registering these structures of interest between a brain atlas and the patient image. Here we aim to improve the results of the state of the art targeting methods and at the same time to reduce the computational time. Our simultaneous segmentation and registration model shows mean STN localization errors statistically similar to the most performing registration algorithms tested so far and to the targeting expert’s variability. Moreover, the computational time of our registration method is much lower, which is a worthwhile improvement from a clinical point of view
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3D semiconducting nanostructures via inverse lipid cubic phases.
Well-ordered and highly interconnected 3D semiconducting nanostructures of bismuth sulphide were prepared from inverse cubic lipid mesophases. This route offers significant advantages in terms of mild conditions, ease of use and electrode architecture over other routes to nanomaterials synthesis for device applications. The resulting 3D bicontinous nanowire network films exhibited a single diamond topology of symmetry Fd3m (Q227) which was verified by Small angle X-ray scattering (SAXS) and Transmission electron microscopy (TEM) and holds great promise for potential applications in optoelectronics, photovoltaics and thermoelectrics
Promoting advance planning for health care and research among older adults: A randomized controlled trial
<p>Abstract</p> <p>Background</p> <p>Family members are often required to act as substitute decision-makers when health care or research participation decisions must be made for an incapacitated relative. Yet most families are unable to accurately predict older adult preferences regarding future health care and willingness to engage in research studies. Discussion and documentation of preferences could improve proxies' abilities to decide for their loved ones. This trial assesses the efficacy of an advance planning intervention in improving the accuracy of substitute decision-making and increasing the frequency of documented preferences for health care and research. It also investigates the financial impact on the healthcare system of improving substitute decision-making.</p> <p>Methods/Design</p> <p>Dyads (<it>n </it>= 240) comprising an older adult and his/her self-selected proxy are randomly allocated to the experimental or control group, after stratification for type of designated proxy and self-report of prior documentation of healthcare preferences. At baseline, clinical and research vignettes are used to elicit older adult preferences and assess the ability of their proxy to predict those preferences. Responses are elicited under four health states, ranging from the subject's current health state to severe dementia. For each state, we estimated the public costs of the healthcare services that would typically be provided to a patient under these scenarios. Experimental dyads are visited at home, twice, by a specially trained facilitator who communicates the dyad-specific results of the concordance assessment, helps older adults convey their wishes to their proxies, and offers assistance in completing a guide entitled <it>My Preferences </it>that we designed specifically for that purpose. In between these meetings, experimental dyads attend a group information session about <it>My Preferences</it>. Control dyads attend three monthly workshops aimed at promoting healthy behaviors. Concordance assessments are repeated at the end of the intervention and 6 months later to assess improvement in predictive accuracy and cost savings, if any. Copies of completed guides are made at the time of these assessments.</p> <p>Discussion</p> <p>This study will determine whether the tested intervention guides proxies in making decisions that concur with those of older adults, motivates the latter to record their wishes in writing, and yields savings for the healthcare system.</p> <p>Trial Registration</p> <p><a href="http://www.controlled-trials.com/ISRCTN89993391">ISRCTN89993391</a></p
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