GTV<Emphasis Type="SmallCaps">cut</Emphasis> for neuro-radiosurgery treatment planning: an MRI brain cancer seeded image segmentation method based on a cellular automata model

Despite of the development of advanced segmentation techniques, achieving accurate and reproducible gross tumor volume (GTV) segmentation results is still an important challenge in neuro-radiosurgery. Nowadays, magnetic resonance imaging (MRI) is the most prominent modality in radiation therapy for soft-tissue anatomical districts. Gamma Knife stereotactic neuro-radiosurgery is a minimally invasive technology for dealing with inaccessible or insufficiently treated tumors with traditional surgery or radiotherapy. During a treatment planning phase, the GTV is generally contoured by experienced neurosurgeons and radiation oncologists using fully manual segmentation procedures on MR images. Unfortunately, this operative methodology is definitely time-expensive and operator-dependent. Delineation result repeatability, in terms of both intra- and inter-operator reliability, can be achieved only by using computer-assisted approaches. In this paper a novel semi-automatic seeded image segmentation method, based on a cellular automata model, for MRI brain cancer detection and delineation is proposed. This approach, called GTVcut, employs an adaptive seed selection strategy and helps to segment the GTV, by identifying the target volume to be treated using the Gamma Knife device. The accuracy of GTVcut was evaluated on a dataset composed of 32 brain cancers, using both spatial overlap-based and distance-based metrics. The achieved experimental results are very reproducible, showing the effectiveness and the clinical feasibility of the proposed approach.     

Formal methods integration for the specification of dependable distributed systems

This paper describes a real-world case study in the specification and analysis of dependable distributed systems. The case study is an automated transport system with safety requirements. In order to manage the complexity of the problem of specifying the dynamic behavior of the whole system, a compositional approach is used, based on the integration of the trace logic of the Communicating Sequential Processes (CSP) theory, and stochastic Petri nets (SPNs). It is argued that the integration of different formal methods is a useful approach in the definition of practical engineering methodologies for the specification, design and analysis of complex dependable distributed systems.     

Evolutionary neural fuzzy systems for noise cancellation in imagedata

A new class of neural fuzzy filters for removing noise from two-dimensional (2-D) measurement data is presented. The proposed approach combines the advantages of the fuzzy and neural paradigms. The network structure is, in fact, specifically designed to exploit the effectiveness of fuzzy reasoning in removing noise without destroying the useful information embedded in the input data. An easy design of new filters is thus obtained because the neuro-fuzzy approach is capable of automatic acquisition of knowledge for a given network structure. The learning method based on genetic algorithms performs an effective training of the network yielding satisfactory results after a few generations. Experimental results show that the proposed approach is very effective also in the presence of data highly corrupted by noise. The neural fuzzy system is largely able to outperform other methods in the literature including state-of-the-art techniques     

Noise removal from image data using recursive neurofuzzy filters

Neurofuzzy approaches are very promising for nonlinear filtering of noisy images. An original network topology is presented in this work to cope with different noise distributions and mixed noise as well. The multiple-output structure is based on recursive processing. It is able to adapt the filtering action to different kinds of corrupting noise. Fuzzy reasoning embedded into the network structure aims at reducing errors when fine details are processed. Genetic learning yields the appropriate set of network parameters from a collection of training data. Experimental results show that the proposed neurofuzzy technique is very effective and performs significantly better than well-known conventional methods in the literature     

An adaptive finite element scheme to solve fluid-structure vibration problems on non-matching grids

This paper deals with the computation of the vibration modes of a system consisting of a linear elastic solid interacting with an acoustic fluid. A finite element method based on meshes for each medium not matching on the fluid-solid interface is analyzed. Optimal order of convergence is proved for the approximation of the eigenfunctions, as well as a double order for the eigenvalues. Numerical tests confirming the theoretical results and showing the advantage of using non-matching grids are reported. Finally, an a posteriori error estimator for this method is introduced and combined with a mesh refinement strategy. The efficiency of this adaptive technique is tested with further numerical experiments. Received: 30 January 2001 / Accepted: 30 May 2001     

Imaging by microwave holography through aberrating media

Imaging through random aberrating media can be of interest not only in optics but also in microwaves or in acoustics. However, the holographic techniques applied in optics cannot be readily extended to microwaves without essential modifications. A different holographic method is here proposed which seems convenient at microwaves. The image is obtained by the product of the aberrated hologram with another compensating for the aberration. In the experiments two different procedures have been followed to perform the product of the two holograms, the optical and the electronic multiplication. The results obtained with the two procedures are shown, one of which allows the correction of time variant aberrations. With this technique there is no limitation in the off-set angles of the reference waves that could be also obtained by locally produced signals and no coherence is requested between the object and the compensating wave. The technique could be of interest, for instance, in plasma diagnostic and geophysical problems.     

Current basis for the ultrastructural clinical diagnosis of tumors: A review

The ultrastructural diagnosis of tumors requires a careful analysis that should be done in an orderly fashion. It requires precise planning from the time of specimen collection to the selection of the area to be examined. Pictures must be taken systematically and every micrograph should allow to answer whether the number of cells photographed is adequate; whether mitoses are present, what is the pattern of the tumor; what is the appearance of the cell membrane; whether the cells are joined by junctional complexes; whether free surfaces possess microvilli or cilia; what organelles are present and how they are distributed; whether there are secretory granules, melanosomes, or other cytoplasmic elements. Nuclear and nucleolar size and shape have to be taken into consideration. The composition of the interstitial extracellular matrix is important in certain types of tumors. Although these questions are not the only ones to be addressed, their use in a logical fashion is helpful when it concerns the ultrastructural diagnosis.     

Negative myoclonic status due to antiepileptic drug tapering: report of three cases

PURPOSE: Epileptic negative myoclonus (ENM) has been increasingly recognized in different epilepsies, but the reasons for its appearance and prognosis remain uncertain. We report 3 patients who developed de novo, almost continuous ENM, triggered by antiepileptic drug (AED) tapering, that resolved with treatment. METHODS: Three patients aged 16, 19, and 65 years with a 13- to 36-year history of partial epilepsy were receiving a therapeutic dosage of carbamazepine or phenobarbital plus either clobazam (CLB) or valproate (VPA). None had previously had ENM. Forty-eight to 72 h after CLB or VPA withdrawal, the habitual seizures recurred. The patient also began to report repetitive postural lapses of one or more limbs that interfered with eating or writing. At this time, each patient underwent polygraphy with simultaneous surface electromyography (EMG) of deltoid, biceps, and triceps muscles and of the wrist extensor and flexor bilaterally. RESULTS: In all patients, EEGs demonstrated almost continuous epileptiform discharges whose spatial distribution was similar to that observed before ENM appearance. Polygraphic recordings showed repetitive loss of postural EMG activity in one or more limbs, 100-400 ms in duration, which occurred in conjunction with the spike-waves. One milligram of clonazepam intravenously always terminated ENM status, which has not recurred in the ensuing 9-36 months. CONCLUSIONS: ENM may emerge as a new type of seizure due to tapering of AED therapy. This effect is possibly related to the great activation of epileptiform activity with consequent interference with cortical activity.