| 11. |
- Johansson, Karl Henrik, et al.
(författare)
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Limit cycles with chattering in relay feedback systems
- 2002
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Ingår i: IEEE Transactions on Automatic Control. - 0018-9286. ; 47:9, s. 1414-1423
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Tidskriftsartikel (refereegranskat)abstract
- Relay feedback has a large variety of applications in control engineering. Several interesting phenomena occur in simple relay systems. In the paper, scalar linear systems with relay feedback are analyzed. It is shown that a limit cycle where part of the limit cycle consists of fast relay switchings can occur. This chattering is analyzed in detail and conditions for approximating it by a sliding mode are derived. A result on existence of limit cycles with chattering is given, and it is shown that the limit cycles can have arbitrarily many relay switchings each period. Limit cycles with regular sliding modes are also discussed. Examples illustrate the results.
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| 12. |
- Källén, Hanna, et al.
(författare)
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Towards Grading Gleason Score using Generically Trained Deep convolutional Neural Networks
- 2016
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Ingår i: 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781479923496 - 9781479923502 ; 2016-June, s. 1163-1167
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Konferensbidrag (refereegranskat)abstract
- We developed an automatic algorithm with the purpose to assist pathologists to report Gleason score on malignant prostatic adenocarcinoma specimen. In order to detect and classify the cancerous tissue, a deep convolutional neural network that had been pre-trained on a large set of photographic images was used. A specific aim was to support intuitive interaction with the result, to let pathologists adjust and correct the output. Therefore, we have designed an algorithm that makes a spatial classification of the whole slide into the same growth patterns as pathologists do. The 22-layer network was cut at an earlier layer and the output from that layer was used to train both a random forest classifier and a support vector machines classifier. At a specific layer a small patch of the image was used to calculate a feature vector and an image is represented by a number of those vectors. We have classified both the individual patches and the entire images. The classification results were compared for different scales of the images and feature vectors from two different layers from the network. Testing was made on a dataset consisting of 213 images, all containing a single class, benign tissue or Gleason score 3-5. Using 10-fold cross validation the accuracy per patch was 81 %. For whole images, the accuracy was increased to 89 %.
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| 13. |
- Landgren, Matilda, et al.
(författare)
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An Automated System for the Detection and Diagnosis of Kidney Lesions in Children from Scintigraphy Images
- 2011
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Ingår i: Lecture Notes in Computer Science. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 0302-9743 .- 1611-3349. - 9783642212277 - 9783642212260 ; 6688, s. 489-500
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Konferensbidrag (refereegranskat)abstract
- Designing a system for computer aided diagnosis is a complex procedure requiring an understanding of the biology of the disease, insight into hospital workflow and awareness of available technical solutions. This paper aims to show that a valuable system can be designed for diagnosing kidney lesions in children and adolescents from 99m Tc-DMSA scintigraphy images. We present the chain of analysis and provide a discussion of its performance. On a per-lesion basis, the classification reached an ROC-curve area of 0.96 (sensitivity/specificity e.g. 97%/85%) measured using an independent test group consisting of 56 patients with 730 candidate lesions. We conclude that the presented system for diagnostic support has the potential of increasing the quality of care regarding this type of examination.
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| 14. |
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| 15. |
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| 16. |
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Projects in History of Automatic Control
- 1997
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This report summarizes the projects in the course History of Control given in the spring of 1996. There was a standard project whose purpose was to give some perspective on the recent developments of the field through study of the contents of the major conferences in Automatic Control. Some students also suggested their own projects, development of an interactive representation of the history of control (The Control Tree) and reflection on the development of control through some awards. Then projects were performed in groups.
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| 17. |
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| 18. |
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| 19. |
- Ståhl, Daniel, et al.
(författare)
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Automatic Compartment Modelling and Segmentation for Dynamical Renal Scintigraphies
- 2011
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Ingår i: Lecture Notes in Computer Science. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 1611-3349 .- 0302-9743. - 9783642212260 - 9783642212277 ; 6688, s. 557-568
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Konferensbidrag (refereegranskat)abstract
- Time-resolved medical data has important applications in a large variety of medical applications. In this paper we study automatic analysis of dynamical renal scintigraphies. The traditional analysis pipeline for dynamical renal scintigraphies is to use manual or semiautomatic methods for segmentation of pixels into physical compartments, extract their corresponding time-activity curves and then compute the parameters that are relevant for medical assessment. In this paper we present a fully automatic system that incorporates spatial smoothing constraints, compartment modelling and positivity constraints to produce an interpretation of the full time-resolved data. The method has been tested on renal dynamical scintigraphies with promising results. It is shown that the method indeed produces more compact representations, while keeping the residual of fit low. The parameters of the time activity curve, such as peak-time and time for half activity from peak, are compared between the previous semiautomatic method and the method presented in this paper. It is also shown how to obtain new and clinically relevant features using our novel system.
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| 20. |
- Weegar, Rebecka, et al.
(författare)
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Linking Entities Across Images and Text
- 2015
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Ingår i: Proceedings of the 19th Conference on Computational Language Learning. - Stroudsburg, PA, USA : Association for Computational Linguistics. - 9781941643778 ; , s. 185-193
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Konferensbidrag (refereegranskat)abstract
- This paper describes a set of methods to link entities across images and text. Asa corpus, we used a data set of images, where each image is commented by a short caption and where the regions in the images are manually segmented and labeled with a category. We extracted the entity mentions from the captions and we computed a semantic similarity between the mentions and the region labels. We also measured the statistical associations between these mentions and the labels and we combined them with the semantic similarity to produce mappings in the form of pairs consisting of a region label and a caption entity. In a second step, we used the syntactic relationships between the mentions and the spatial relationships between the regions to rerank the lists of candidate mappings. To evaluate our methods, we annotated a test set of 200 images, where we manually linked the image regions to their corresponding mentions in the captions. Eventually, we could match objects in pictures to their correct mentions for nearly 89 percent of the segments, when such a matching exists.
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