Molham MOSHANTAT, Saeid KARAMZADEH

Ayrık Dalgacık Dönüşümü ile CT ve MRI Medikal Görüntü Füzyonu

Günümüzde medikal görüntülerin teşhis ve tedavide büyük bir rol oynadığı aşikardır. Daha fazla bilgi taşıyan ve birden fazla görüntünün füzyonundan ulaşan bir görüntü bu sürece katkı sağlayacaktır. Bu çalışmada ise, CT ve MRI görüntülerinin füzyonu için, literatürde bilinen en iyi füzyon yöntemlerinden bir olan dalgacık dönüşümü uygulanmıştır. Farklı dalgacık dönüşümleri kullanılıp sonuçları sunulmuştur. Çıkan sonuçların karşılaştırılması için entropi ve sinyal, gürültü oranı (SNR) ölçülüp verilmiştir.

CT and MRI Medical Image Fusion Using Discrete Wavelet Transform

In these days, using medical image is very important in hospitals. These medical images give a lot of data about human body for example Computed Tomography (CT) identifies the bone structure, Magnetic Resonance Image (MRI) image gives information about tissue data, Positron on Emission Tomography (PET) and Single photon release computed tomography (SPECT) give human body functionality data. but these images can't give clear data image for disease diagnosis and treatment planning. So, these different modality complementary data for effective disease analysis is required. In this work we fused two images (CT and MRI) by using discrete wavelet transform then applied this transform on all types of wavelets (haar, Daubechies, Mexican Hat, Symlets, Morlet, Shannon).

PDF

___

A. Soma Sekhar, Dr.M.N. Giri Prasad., A Novel Approach of Image Fusion on MR and CT Images Using Wavelet Transforms, 3rd International Conference on Electronics Computer Technology, April (2011) 12 -86 DOI: 10.1109/ICECTECH.2011.5941881.
H. H. Wang., A new multiwavelet-based approach to image fusion, Journal of Mathematical Imaging and Vision, 21 (2004) 177-180.
Bernd Fischer, Jan Modersitzki., Curvature Based Image Registration, Journal of Mathematical Imaging and Vision, 18-1 (2003) 81–85.
Peter Rogelj and Stanislav Kovacic., Similarity Measures for Non- Rigid Registration, Ministry of Science and Technology of the Republic of Slovenia, Research program, feb. (2001) 82-91.
Ligia Chiorean, Mircea-Florin Vaida., Medical Image Fusion Based on Discrete Wavelet Transform Using Java Technology, 31st Int. Conf. on Information Technology Interfaces, June (2009).
NEMA Publications., Digital Imaging and Communications in Medicine (DICOM), journal of digtal medcicin , Ver. 8.0 (2008) 8-16.
https://www.dicomlibrary.com 12.11.2018 11:45.
M. Hub, M.L. Kessler, and C.P. Karger., A stochastic approach to estimate the uncertainty involved in B-spline image registration, MedImg, 28-11 (2009) 1708–1716.
J.V.Chapnick, M.E.Noz, G.Q. Maguire, E.L.Kramer, J.J.Sanger, B.A.Birnbaum, A.J.Megibow., Techniques of Multimodality Image Registration, Proceedings of the IEEE nineteenth Annual North East Bioengineeering conference, 18-19 March (1993) 221-222.
J. B. Antoine Maintz and Max A. Viergever., A Survey of Medical Image Registration, Medical Image Analysis 2-1 (1998) 1-36.
Brown Gottesfeld L., A survey of image Registration Techniques, ACM Computing surveys, 24-4 (1992) 325-376.
Rahul S.Shınde, Altaaf O.Mulani., Bıomedıcal Image Fusıon Usıng Wavelet Transform, 2-10 (2015) 50-53.
P. A. Van Den Elsen, E. J. D. Pol and M. A. Viergever., Medical image matching: a review with classification, IEEE Engineering in medicine and biology, march (1993) 26-39.
Pelizzari CA, Chen GTY, Spelbring DR, Weichselbaum RR, Chen CT. Accurate 3-dimensional registration of CT, PET, and/or MR images of the brain. J Comput Assist Tomogr, Jan-Feb. (1989) 13-20.