Frank Schmitt

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OBJECTIVE To demonstrate the feasibility of the use of digital images to document routine cases and to perform diagnostic quality assessment. METHODS Pathologists documented cases by acquiring up to 12 digital images per case. The images were sampled at 25:1, 50:1, 100:1, 200:1, or 400:1 magnifications, according to adequacy in aiding diagnosis. After(More)
Virtual high-throughput screening of molecular databases and in particular high-throughput protein-ligand docking are both common methodologies that identify and enrich hits in the early stages of the drug design process. Current protein-ligand docking algorithms often implement a program-specific model for protein-ligand interaction geometries. However, in(More)
We present evaluation results with focus on combined image and efficiency performance of the Gradient Network Method to segment color images, especially images showing outdoor scenes. A brief review of the techniques, Gradient Network Method and Color Structure Code, is also presented. Different region-growing segmentation results are compared against(More)
The objective of this paper is to evaluate a new combined approach intended for reliable color image segmentation, in particular images presenting color structures with strong but continuous color or luminosity changes, such as commonly found in outdoors scenes. The approach combines an enhanced version of the Gradient Network Method, GNM2, with common(More)
OBJECTIVE To develop a program to assist the pathologist in the acquisition and evaluation of digital images to determine microvessel density (MVD) in tissues. STUDY DESIGN Ten cases of breast cancer with a high degree of neovascularization were selected. A standard immunohistochemical method was used to highlight the microvessels (monoclonal anti-factor(More)
The 3D Cell Structure Code (3D-CSC) is a fast region growing technique. However, directly adapted for segmentation of magnetic resonance (MR) brain images it has some limitations due to the variability of brain anatomical structure and the degradation of MR images by intensity inhomogeneities and noise. In this paper an improved approach is proposed. It(More)