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Background Certolizumab pegol (CZP) is an Fc-free, PEGylated anti-tumor necrosis factor biologic. Objectives To report three-year outcomes from the CIMPACT (NCT02346240) phase 3, CZP in moderate to severe plaque psoriasis, randomized controlled trial. Methods Adults were randomized 3:3:3:1 to CZP 200 mg every other week (Q2W), CZP 400 mg Q2W, etanercept biweekly, or placebo. At Week 16, CZP- and etanercept-treated PASI 75 responders were re-randomized to CZP 200 mg Q2W, CZP 400 mg Q4W, CZP 400 mg Q2W, or placebo for maintenance treatment; PASI 75 non-responders entered an open-label escape CZP 400 mg Q2W arm. Patients entering the open-label extension (OLE; Weeks 48-144) from blinded treatment received CZP 200 mg Q2W. Results Double-blinded results have been reported previously. 261 patients received 200 mg Q2W upon OLE entry. PASI 75 response was maintained in patients continuing 200 mg Q2W treatment through Weeks 16-144 (Week 144: 96.2%). In patients dosed down at Week 48 (double-blinded 400 to 200 mg Q2W), PASI 75 decreased (Week 48: 98.7%; Week 144: 85.9%). In patients who received placebo through Weeks 16-48, PASI 75 response decreased (Week 48: 60.4%), then increased following Week 48 switch to 200 mg Q2W (Week 144: 95.1%). 48 and 36 patients initially randomized to 200 and 400 mg Q2W, respectively, were Week 16 PASI 75 non-responders and entered the escape arm; at Week 144, 71.8% and 78.2% achieved PASI 75. No new safety signals were identified. Conclusions Response to CZP was durable over three years; no new safety signals were identified.

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Image databases that allow retrieval of data by referring to the image contents need an image analysis module. In this paper we will describe the features of ‘I-see’, a knowledge-based software environment that we have designed specifically for image analysis. We will assess the usefulness of this tool for the development of interpretation modules for image databases. Two important research topics are investigated. First, precompilation of the image contents is necessary for efficient retrieval. Second, query by image contents must allow access to objects and situations represented in the images. Our approach will be to look at these database functionalities in general image analysis terms. In this sense, precompilation will be considered as a special case of image interpretation, query specification as a form of model description while query retrieval will be viewed in terms of model instantiation and selection. Although the ‘I-see’ tool already contains features that can be used as image database parts, the paper will consider the tool as a research platform rather than as an image database module.

Knowledge based image analysis is a combination of digital signal processing and symbolic reasoning. In this paper, we will look at some problems connected to the symbolic reasoning approach to image interpretation and see how an iconic representation can help to solve some of them. We will show that many of the features and problems connected with both symbolic and iconic representation are complementary.

Road networks extracted from multi-temporal SPOT images of the same scene are matched to collect evidence for individual road segments. The Dempster-Shafer theory is applied to find a degree of confirmation for a road segment in one network based on its corresponding lines in the other networks.

The paper describes a software environment in development that supports the implementation of image understanding applications. The described environment, called I-see, is implemented on top of the object oriented KEE ∗ system and focuses on the iconical representation and exploration of visual data. The system offers an interface between the high-level symbolic reasoning mechanisms of KEE and the raw image data and iconically represented image models or segmentation results.

A software environment that supports the implementation of image understanding applications is described. The environment, called I-see, is implemented on top of the object-oriented KEE system and focuses on the iconic representation and exploration of visual data. The system offers an interface between the high-level symbolic reasoning mechanisms of KEE and the raw image data and iconically represented image models or segmentation results. An example problem of interpreting satellite images shows the use of this iconically represented knowledge in the form of a terrain elevation image. In this specific example, the iconic representation could be used directly without the need for a complementary symbolic description. The iconic and symbolic representation schemes can be used to supplement each other and can be related by the use of label images. >

Currently both statistical and neural classifiers are being used for the classification of multispectral satellite imagery. Because both classifier types are being used as 'black boxes' and because they are values based on different mathematical models the reasons for their different performance levels are not well understood. The authors have used visualization of class decision boundaries in feature space as a means to gain insight into the classification processes. >

Long-term ingestion of tolamolol led to severe poikiloderma with microscopic features similar to those of premycosis.

SummaryOral administration of tranexamic acid, in a dosage of 3 g daily from the first day of menstruation onwards, significantly decreases menstrual haemoglobin loss in women with so-called essential menorrhagia.The frequency of side-effects reported did not differ between “active” and “placebo” periods.

A patient presented with only one tumor of mycosis fungoides and remained free of any lesion 5 years after conventional radiotherapy.

Automated delineation of linear cultural structures can help to improve the classification of remotely-sensed images. This topic also provides an excellent testbed for knowledge-based computer vision research. In this paper, a road network extraction system, useful on SPOT satellite images, is described. By applying semantic model-fitting operators, an initial spatial segmentation is obtained. To analyse the resulting primal road network, declaratively stated knowledge about generic appearances of roads and crossroads on SPOT images is used. As a result a more detailed description of the network can be obtained. Advantages and drawbacks of the use of existing knowledge base tools for this computer vision task are reported.

Due to the high availability of aerial images, the automated interpretation has become an increasing need. One of the application fields is the interpretation of aerial images of cities. The interpretation allows for a better understanding of the traffic patterns. We have chosen this application because its a challenging task involving complex images. This paper describes the need for techniques beyond the pure numerical and statistical methods. It describes how the use of symbolic oriented rules combined with humanlike reasoning mechanisms can drastically improve results.

Work in progress on knowledge-based blood vessel segmentation of subtraction angiograms is reported. The proposed approach is centered around different modular stages which are linked through the concept of a multi-layered image representation. At the bottom level classical image processing techniques are used to extract edges, center lines and bars. At the intermediate stage, low-level geometrical knowledge has been encoded to construct blood vessel segments. The higher levels will contain general blood vessel knowledge and application domain-dependent knowledge in order to create a final representation of the blood vessels. Although the system is only partly implemented, a result already of practical use will be discussed.

Due to the resolution of current satellite imagery (e.g. SPOT), the extraction of roads and linear networks from satellite data has become a feasible - although labour-intensive - task for a human expert. This interpretation problem relies on structural image recognition as well as on expertise in combining data sources external to the image data (e.g. topography, landcover classification). In this paper different knowledge sources employed by human interpreters are discussed. Ways to implement these sources using current knowledge-based tools are suggested. A practical case study of knowledge integration is described.