Quantitative tests-based assessment of biomedical image enhancement procedures

• Autorzy: Przytulska M. , Kulikowski J. L.

Identyfikatory

DOI

10.1016/j.bbe.2015.10.011

• Języki publikacji: EN

Abstrakty

EN

This paper describes a novel method of images enhancement procedures evaluation. A necessity of such method follows from the fact that the results of morphological or statistical image analysis in medical and/or technological applications strongly depend on the effectiveness of image preprocessing. The proposed method is based on standard images called testing sets composed of several basic patterns. Filtered testing sets are compared to basic patterns and the averaged distances between them are used as primary filtering quality scores. Then, they are used to calculation of several secondary parameters called image restoration errors. The image restoration errors make possible separate characterization of filters' ability to improve image contrast, discrimination of small details or neglect the influence of image parallel shifts on the visibility of image details. Practical application of the proposed method is illustrated by example of comparison of the quality of three exemplary filters: a one based on second-level morphological spectra, Laplace and Sobel, filters. Similar comparison has been performed on the same filters combined with image binary thresholding procedures. At last, the numerical evaluation is compared to visual filters evaluation based on the results of NMR brain image enhancement reached by using different filtering methods.

Słowa kluczowe

EN

computer aided image processing; biomedical image enhancement; image filtering; multiaspect filters evaluation

PL

komputerowa obróbka obrazu; jakość obrazu; filtracja obrazu

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2016
• Tom: Vol. 36, no. 1
• Strony: 205--216
• Opis fizyczny: Bibliogr. 16 poz., rys., tab., wykr.

Twórcy

autor

Przytulska M.

• Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Trojdena 4, 02-109 Warsaw, Poland

autor

Kulikowski J. L.

• Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Trojdena 4, 02-109 Warsaw, Poland

Bibliografia

• [1] González R, Woods R. Digital image processing. New York: Pearson/Prentice Hall; 2008.
• [2] Sonka M, Hlavac V, Boyle R. Image processing analysis and machine vision. Toronto: Thomson; 2008.
• [3] Russ JC. The image processing handbook. 6th ed. Boca Raton: CRC Press; 2011. p. 433–506.
• [4] Bovik A, editor. Handbook of video & image processing. London: Academic Press; 2000.
• [5] Piętka D, Dulewicz A, Jaszczak P. Removing artifacts from microscopic images of cytological smears. A shape-based approach. In: Kurzyński M, Woźniak M, Żołnierek A, editors. Computer recognition systems, advances in soft computing. Puchała E: Springer; 2005. p. 661–9.
• [6] Demirkaya Ö, Asyali M, Sahoo P. Image processing with MATLAB: applications in medicine and biology. Taylor & Francis; 2009.
• [7] Kulikowski JL, Przytulska M, Wierzbicka D, Direct Filtering. Enhancement of biomedical images based on morphological spectra. In: Kurzyński M, Woźniak M, editors. Computer recognition systems 3 advances in soft computing, vol. 57. Heidelberg: Springer; 2009. p. 159–66.
• [8] Pitas I. Digital image processing algorithms and applications. New York: A Wiley-Interscience Publication; 2000. p. 323–34.
• [9] Wang Z, Bovik A, Sheikh HR, Simoncelli EP. Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 2004;13(4).
• [10] Kulikowski JL, Przytulska M, Wierzbicka D. Description of biomedical textures by statistical properties of their morphological spectra. Biocybern Biomed Eng 2009;30(3):19–34.
• [11] Przytulska M, Kulikowski JL, Wierzbicka D. Evaluation of effectiveness of high-pass image filtering methods (in Polish). Materials of National Conference on Biocybernetics and Biomedical Engineering; 2013.
• [12] Pratt WK. Digital image processing. Now York: John Wiley & Sons; 2007.
• [13] Przytulska M, Kulikowski JL, Wierzbicka D. Biomedical images enhancement based on the properties of morphological spectra. Biocybern Biomed Eng 2014;10.
• [14] Van Meir EG, Hadjipanayis CG, Norden AD, Shu HK, Wen PY, Olson JJ. Exciting new advances in neuro- oncology. The avenue to a cure for malignant glioma. CA Cancer J Clin 2010;60(3):166–93.
• [15] https://encryptedtbn1. gstatic. com/images?q=tbn: ANd9GcQZAgPNiPVZuWN3HshI AIrXCV4y88Z7W7lH50qBL3fyBC0JE9pa.
• [16] http://www.forum-onkologiczne.com.pl/forum/ rak-piersi-uogolniony-vt4939.htm.

Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.