| dr hab. inż. Leszek Chmielewski |
 |
Habilitacja
| 2008-03-27 | Metody akumulacji danych w analizie obrazów cyfrowych |
Ostatnie publikacje
| 1. | Bator M.♦, Chmielewski L.J., Finding regions of interest for cancerous masses enhanced by elimination of linear structures and considerations on detection correctness measures in mammography, PATTERN ANALYSIS AND APPLICATIONS, ISSN: 1433-7541, Vol.12, pp.377-390, 2009 |  | 20p. | ||
| 2. | Chmielewski L.J., Accumulation methods in the processing of difficult images, JOURNAL OF MEDICAL INFORMATICS AND TECHNOLOGIES, ISSN: 1642-6037, Vol.12, pp.40503-0, 2008 Streszczenie: The accumulation methods emerged in close relation to the development of the Hough transform (HT). The application of some far reaching generalizations of the HT will be presented. The accumulation principle will be taken as a starting point: Accumulate the relevant data from possibly many, possibly competent sources. This principle is known and widely used in image processing, mainly in the methods related to the HT. The principle is in opposition to the tendency to compress the image data as early in the processing as possible. The accumulation principle is a recommendation to utilize the redundancy in the image data in a specific way and should be applied when the images are difficult to process due to their low quality. The basic data structure is the fuzzy histogram, which is in fact an experimentally obtained approximation of the probability density of the phenomenon of interest. The concepts of a degree of fuzzification and the weakly and strongly fuzzified histograms will be introduced. A number of solutions found with the use of the accumulation principle will be presented. In the examples and tests, biomedical images will be used. Such images are challenging because the objects imaged are irregular and the quality of the images is usually limited in a natural way by the imaging modalities used. The accumulation methods are a good solution to the problem of analysis of such images. Afiliacje autorów:
| | |||
| 3. | Chmielewski L.J., Fuzzy histograms, weak fuzzification and accumulation of periodic quantities. Application in two accumulation-based image processing methods, PATTERN ANALYSIS AND APPLICATIONS, ISSN: 1433-7541, DOI: 10.1007/s10044-006-0037-7, Vol.9, No.2, pp.189-210, 2006 Streszczenie: The influence of the scale of a fuzzy membership function used to fuzzify a histogram is analysed. It is shown that for a class of fuzzifying functions it is possible to indicate the limit for fuzzification, at which the mode of the histogram equals the mean of the data accumulated in it. The fuzzification functions for which this appears are: the quadratic function for aperiodic histograms and the cosine square function for periodic ones. The scaled and clipped versions of these functions can be used to control the degree of fuzzification belonging to the interval [0,1]. While the quadratic function is related to the widely known Huber-type clipped mean or the kernel function derived from the Epanechnikov kernel, the clipped cosine square seems to be less known. The indications for using strong or weak fuzzification, according to the value of the fuzzification degree, are justified by examples in two applications: classic Hough transform-based image registration and novel accumulation-based line detection. Typically, the weak fuzzification is recommended. The images used are related to simulation images from teleradiotherapy and to mammographic images. Słowa kluczowe: Fuzzy histogram, Accumulation, Scale, Mode to mean transition, Limit fuzzification, Periodic histogram, Line detection, Mammograms, Image registration Afiliacje autorów:
|  | |||
| 4. | Kukołowicz P.F.♦, Dąbrowski A., Gut P.♦, Chmielewski L.J., Wieczorek A.♦, Evaluation of set-up deviations during the irradiation of patients suffering from breast cancer treated with two different techniques, RADIOTHERAPY AND ONCOLOGY, ISSN: 0167-8140, Vol.75, No.1, pp.22-27, 2005 | |
Lista ostatnich monografii
| 1. 100 | Chmielewski L.J., Metody akumulacji danych w analizie obrazów cyfrowych, Akademicka Oficyna Wydawnicza EXIT, pp.1-268, 2006 |
Lista rozdziałów w ostatnich monografiach
| 1. 139 | Bator M.♦, Chmielewski L.J., Computer recognition systems 2, Soft computing, rozdział: Elimination of linear structures as an attempt to improve the specificity of cancerous mass detection in mammograms, Springer, Kurzynski M., Puchala E., Wozniak M., Zolnierek A. (Eds.), 45, pp.596-603, 2007 | |
| 2. 141 | Chmielewski L.J., Computer vision and graphics, Computational imaging and vision, rozdział: Detection of non-parametric lines by evidence accumulation: finding blood vessels in mammograms, Springer, Wojciechowski K., Smolka B., Palus H., Kozera R.S., Skarbek W., Noakes L. (Eds.), 32, pp.373-380, 2006 | |
| 3. 129 | Chmielewski L.J., Advances in Soft Computing, Computer Recognition Systems, rozdział: Scale and direction invariance of the evidence accumulation-based line detection algorithm, Springer, Kurzyński M., Puchała E., Woźniak M., Żołnierek A. (Eds.), pp.363-370, 2005 | |
| 4. 130 | Chmielewski L.J., Advances in Soft Computing, Computer Recognition Systems, rozdział: Specification of the evidence accumulation-based line detection algorithm, Springer, Kurzyński M., Puchała E., Woźniak M., Żołnierek A. (Eds.), pp.355-362, 2005 |