Combination median filter

A detail- and structure-preserving smoothing filter is introduced. It is called the combination median filter as it uses directional median, multilevel median, and median filters to smooth different regions of the image. The decision about the region is made by robust Dixon's r-test which is well known in statistics for outlier detection. The threshold value of Dixon's test can be kept constant. As a result, the filtering algorithm operates like a quasi-nonadaptive filter, and no computation of local statistics is involved. Some properties of the filter as well as detailed experimental results that demonstrate its superior performance are presented.

Eating epilepsy: a study of twenty cases

Twenty cases of eating epilepsy have been studied over a period of 5 years (1985-1989). Males outnumbered females (4:1). Heavy meal comprising conventional Indian diet (viz, rice, vegetables, etc), was found to be the most important provocating factor (14 out of 20 cases). The attacks occurred at lunch time in most cases (15). Thirteen cases had generalised seizures. Electro-encephalogram showed focal changes in 10 cases, generalised changes in 6 cases, while 4 cases had normal electro-encephalogram. Computerised tomography scan was normal in all the cases (7) when it was done.

Cell surface transport, oligomerization, and endocytosis of chimeric type II glycoproteins: role of cytoplasmic and anchor domains

We investigated the role of cytoplasmic and anchor domains of type II glycoproteins in intracellular transport, oligomerization, and endocytosis by expressing the wild-type and chimeric genes in mammalian cells. Chimeric genes were constructed by exchanging the DNA segments that encode the cytoplasmic and anchor domains between the human influenza virus (A/WSN/33) neuraminidase (NA) and transferrin receptor (TR). The chimeric proteins in which domains were exchanged precisely were productively targeted to the cell surface. However, the proteins appeared to assemble differently in the intracellular compartment. For example, while TR existed predominantly as a dimer, NATR delta 90, containing the cytoplasmic and signal-anchor domains of NA and the ectodomain of TR, was present as a tetramer, a dimer, and a monomer. Similarly, the influenza virus NA existed predominantly as a tetramer but TRNA delta 35, in which the cytoplasmic and signal-anchor domains of TR were joined to the ectodomain of NA, existed predominantly as a dimer, suggesting that the cytoplasmic and anchor domains of type II glycoproteins affect the subunit assembly of heterologous ectodomains. In addition, we analyzed the role of the cytoplasmic domain in endocytosis. NA and NATR delta 90 did not undergo endocytosis, whereas both TR and TRNA delta 35 were internalized efficiently, demonstrating that the NH2 cytoplasmic domain of TR was capable of internalizing a heterologous ectodomain (NA) from the cell surface.

Local segmentation of biomedical images

In this paper, a new algorithm for local segmentation of biomedical images is presented. First, a relatively small region is selected for segmentation on the basis of dispersion measurement of local gray values. This small region is then segmented using a segmentation algorithm based on quantization approach. While quantizing a signal, the range of input signal is divided into a number of segments. All signal values within a segment are assigned a unique reconstruction value. In segmentation of gray level images, the problem is to classify or code gray values of the pixels into two or more groups. An N-level threshold selection method for segmentation thus becomes the design of an N-level optimal quantizer. This new approach is suitable for a number of biomedical applications where the objects of interest appear as small and localized in the images. Some experimental results are also provided which illustrate the success of the new scheme.

A new algorithm for image edge extraction using a statistical classifier approach

This correspondence describes a new algorithm for extracting edges from natural images. Starting from a simple image model, the algorithm poses the problem of edge extraction as a statistical classifier problem. The algorithm is capable of extracting and detecting edges from images even in the presence of noise. A step by step mathematical derivation of the algorithm reveals the flexibility of the algorithm with pertinent parameters that can be varied for the specific need of the user. Finally, the proposed edge operator is compared to the well-known Marr-Hildreth's edge operator.