David Pycock

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The Concordance-based Medial Axis Transform (CMAT) presented in this paper is a multiscale medial axis (MMA) algorithm that computes the medial response from grey-level boundary measures. This non-linear operator responds only to symmetric structures, overcoming the limitations of linear medial operators which create “side-lobe” responses for symmetric(More)
Metaphase finding is an essential activity in chromosome analysis, and there is much to gain from its automation. This paper describes software for automatic metaphase finding developed for use as part of a routine clinical chromosome analysis system, principally for samples from blood and amniotic fluid. Since the metaphase finding and analysis programs(More)
Many reports in recent years have described the application of image analysis to cervical smear prescreening. This paper describes a complementary approach to automation in diagnostic cytology. In this approach the image analyzer is programmed to automatically scan a slide, measure preselected morphologic features and store the results. Subsequently, the(More)
A low-cost automatic prescreening system for uterine cancer cytology based on the commerically available MAGISCAN Image Analyser is described. Dispersed hematoxylin-stained samples are viewed with an automated TV microscope. Software has been written to locate cell nuclei at 4 micron resolution and trace each nuclear boundary at 0.5 micron resolution. At(More)
This paper describes a framework for model representation and control intended as the basis of a computer vision system capable of undertaking arbitrary but well defined image interpretation tasks. An inter-related structure of models represents both the visual task and image content. The user defines this structure but not the internal details of all(More)
This paper describes a simple model-based approach to boundary detection for blob shaped objects. A geometric model is used to focus attention on relevant portions of the image during boundary generation. The boundary generated is that which is a globally optimal match to the shape and edge description parameters of the model. The method is illustrated(More)