Adaptive window-based tracking for the detection of membrane structures in kidney electron micrographs

An algorithm for the detection and measurement of the glomerular basement membrane in kidney electron micrographs by image analysis techniques is described. Starting from a user-specified point, local features within a small window are computed to give a feature score. Feature scores for adjacent neighbourhoods are also determined, and windows that satisfy similarity criteria are linked to produce the centerline of the membrane. A region-growing process completes the segmentation procedure. The adaptive and local nature of the algorithm ensures successful segmentation despite the complex and variable characteristics of the micrograph image.     

Autofocusing for tissue microscopy

This paper describes the implementation of autofocusing for tissue microscopy. We first investigate the suitability of several criterion functions for the evaluation of image sharpness. Since tissue sections are invariably stained, we also discuss the selection of the colour component on which autofocusing will be performed. In tissue microscopy, where a section generally comprises multiple layers, it is often not possible to obtain an image that is well focused over the field of view because of the limited depth of field of the objective. We describe focus enhancement algorithms, closely related to the autofocus system, which may be employed to obtain an entirely sharp image.     

A domain operator for binary morphological processing

A new class of morphological operators, the domain operator, is proposed for binary images. The operation is defined with a domain function based on the index function of fuzzy sets. With appropriate definition of the connection weights, the domain operator can implement conventional morphological operations such as dilation, erosion, opening, and closing, as well as other image processing functions such as noise reduction, edge detection, and clump splitting.