[Infiltration of the skull by dedifferentiated cutaneous leiomyosarcoma]. / Infiltration der Schädelkalotte durch ein dedifferenziertes kutanes Leiomyosarkom.

We present a brief report of an 81-year-old man with a pretreated leiomyosarcoma of the skull. Histologically the diagnosis of a dedifferentiated cutaneous leiomyosarcoma with an infiltration of the skull was confirmed. In an interdisciplinary approach together with the University Clinic for Neurosurgery, complete removal of the tumour was performed. Cutaneous leiomyosarcoma are rare tumors of the skin and typically present as slowly growing erythematosus nodes. Because of the risk of metastatic spread, complete micrographically confirmed resection is necessary.

Forward error correction supported 150 Gbit/s error-free wavelength conversion based on cross phase modulation in silicon.

We build a forward error correction (FEC) module and implement it in an optical signal processing experiment. The experiment consists of two cascaded nonlinear optical signal processes, 160 Gbit/s all optical wavelength conversion based on the cross phase modulation (XPM) in a silicon nanowire and subsequent 160 Gbit/s-to-10 Gbit/s demultiplexing in a highly nonlinear fiber (HNLF). The XPM based all optical wavelength conversion in silicon is achieved by off-center filtering the red shifted sideband on the CW probe. We thoroughly demonstrate and verify that the FEC code operates correctly after the optical signal processing, yielding truly error-free 150 Gbit/s (excl. overhead) optically signal processed data after the two cascaded nonlinear processes.

Adaptive partially hidden Markov models with application to bilevel image coding.

Partially hidden Markov models (PHMMs) have previously been introduced. The transition and emission/output probabilities from hidden states, as known from the HMMs, are conditioned on the past. This way, the HMM may be applied to images introducing the dependencies of the second dimension by conditioning. In this paper, the PHMM is extended to multiple sequences with a multiple token version and adaptive versions of PHMM coding are presented. The different versions of the PHMM are applied to lossless bilevel image coding. To reduce and optimize the model cost and size, the contexts are organized in trees and effective quantization of the parameters is introduced. The new coding methods achieve results that are better than the JBIG standard on selected test images, although at the cost of increased complexity. By the minimum description length principle, the methods presented for optimizing the code length may apply as guidance for training (P)HMMs for, e.g., segmentation or recognition purposes. Thereby, the PHMM models provide a new approach to image modeling.

Lossless, near-lossless, and refinement coding of bilevel images.

We present general and unified algorithms for lossy/lossless coding of bilevel images. The compression is realized by applying arithmetic coding to conditional probabilities. As in the current JBIG standard the conditioning may be specified by a template. For better compression, the more general free tree may be used. Loss may be introduced in a preprocess on the encoding side to increase compression. The primary algorithm is a rate-distortion controlled greedy flipping of pixels. Though being general, the algorithms are primarily aimed at material containing half-toned images as a supplement to the specialized soft pattern matching techniques that work better for text. Template based refinement coding is applied for lossy-to-lossless refinement. Introducing only a small amount of loss in half-toned test images, compression is increased by up to a factor of four compared with JBIG. Lossy, lossless, and refinement decoding speed and lossless encoding speed are less than a factor of two slower than JBIG. The (de)coding method is proposed as part of JBIG2, an emerging international standard for lossless/lossy compression of bilevel images.

Tree coding of bilevel images.

Presently, sequential tree coders are the best general purpose bilevel image coders and the best coders of halftoned images. The current ISO standard, Joint Bilevel Image Experts Group (JBIG), is a good example. A sequential tree coder encodes the data by feeding estimates of conditional probabilities to an arithmetic coder. The conditional probabilities are estimated from co-occurrence statistics of past pixels, the statistics are stored in a tree. By organizing the code length calculations properly, a vast number of possible models (trees) reflecting different pixel orderings can be investigated within reasonable time prior to generating the code. A number of general-purpose coders are constructed according to this principle. Rissanen's one-pass algorithm, context, is presented in two modified versions. The baseline is proven to be a universal coder. The faster version, which is one order of magnitude slower than JBIG, obtains excellent and highly robust compression performance. A multipass free tree coding scheme produces superior compression results for all test images. A multipass free template coding scheme produces significantly better results than JBIG for difficult images such as halftones. By utilizing randomized subsampling in the template selection, the speed becomes acceptable for practical image coding.

Filters involving derivatives with application to reconstruction from scanned halftone images.

This paper presents a method for designing finite impulse response (FIR) filters for samples of a 2-D signal, e.g., an image, and its gradient. The filters, which are called blended filters, are decomposable in three filters, each separable in 1-D filters on subsets of the data set. Optimality in the minimum mean square error sense (MMSE) of blended filtering is shown for signals with separable autocorrelation function. Relations between correlation functions for signals and their gradients are derived. Blended filters may be composed from FIR Wiener filters using these relations. Simple blended filters are developed and applied to the problem of gray value image reconstruction from bilevel (scanned) clustered-dot halftone images, which is an application useful in the graphic arts. Reconstruction results are given, showing that reconstruction with higher resolution than the halftone grid is achievable with blended filters.