Sat, 26 Jul 2008 17:17:22 BST CiteULike: jyuh Viel http://www.citeulike.org/user/jyuh/author/Viel CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/user/jyuh/article/2784600 <i>Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society, Vol. 29, No. 5. (July 2005), pp. 333-341.</i><br /><br />The present paper describes a method for autofocusing specifically studied for the acquisition of digital slides, i.e. full histologic and cytologic slides, utilising low-cost equipment. At first, experimentations with some of the most used focus measures and algorithms have been made, in order to choose the most suitable for histologic and cytologic images. Then, a study of the specific features of digital slides has been preliminarily carried out in order to understand the constraints of the domain. These included the capability of autofocusing in an unattended way on thousands of microscope fields, while fast performance is not a strict requirement. Based on the findings, an algorithm based on a dynamic focus position space, with a variance-based focus measure has been adapted to the specific situation. A qualitative and quantitative evaluation of the proposed algorithm allowed us to show that the proposed algorithm is suitable for the acquisition of digital slides, and furthermore it can be implemented starting from a basic microscope with an inexpensive motorised stage. The algorithm is currently implemented into a complete digital slide acquisition system, which is in turn being used for a Quality Assurance Programme in cervicovaginal cytologic screening. A pixel-based autofocusing technique for digital histologic and cytologic slides. V Della Mea F Viel CA Beltrami doi:10.1016/j.compmedimag.2005.02.004 Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society, Vol. 29, No. 5. (July 2005), pp. 333-341. 2008-05-11T16:00:20-00:00 2005 Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society 0895-6111 29 5 333 341 no-tag http://www.citeulike.org/user/jyuh/article/2635998 <i>Statistics in medicine, Vol. 19, No. 17-18. (0 2000), pp. 2217-2241.</i><br /><br />The analysis of small area disease incidence has now developed to a degree where many methods have been proposed. However, there are few studies of the relative merits of the methods available. While many Bayesian models have been examined with respect to prior sensitivity, it is clear that wider comparisons of methods are largely missing from the literature. In this paper we present some preliminary results concerning the goodness-of-fit of a variety of disease mapping methods to simulated data for disease incidence derived from a range of models. These simulated models cover simple risk gradients to more complex true risk structures, including spatial correlation. The main general results presented here show that the gamma-Poisson exchangeable model and the Besag, York and Mollie (BYM) model are most robust across a range of diverse models. Mixture models are less robust. Non-parametric smoothing methods perform badly in general. Linear Bayes methods display behaviour similar to that of the gamma-Poisson methods. Disease mapping models: an empirical evaluation. Disease Mapping Collaborative Group. AB Lawson AB Biggeri D Boehning E Lesaffre JF Viel A Clark P Schlattmann F Divino Statistics in medicine, Vol. 19, No. 17-18. (0 2000), pp. 2217-2241. 2008-04-07T02:47:26-00:00 2000 Statistics in medicine 0277-6715 19 17-18 2217 2241 no-tag