Automatic identification breast cancer using multiresolution algorithm
Abstract
In this paper, we present a multiresolution scheme to detect stellate lesions in mammograms. Multiresolution analysis is used to analyze the images at different frequencies with different resolutions. First we removed the noise from mammograms using Multiresolution analysis and then we detected tumors. Then, using the Embedded Zerotree Wavelet (EZW) algorithm, we compressed denoising mammographic image and showed that by applying the algorithm to detect tumors in the compressed image we obtained the same results as in the case of non-compressed images. Experimental results obtained from the mammographic images of patients recorded in the Clinical Center in Kragujevac, show that using multiresolution algorithm can be detected tumors of different sizes.
Keywords:
Multiresolution analysis of mammograms / Discrete Wavelet Transformation / Embedded zerotree wavelet / Breast cancerSource:
HealthMed, 2011, 5, 6, 2051-2064Publisher:
- Drunpp-Sarajevo, Sarajevo
Funding / projects:
Collections
Institution/Community
Geografski fakultetTY - JOUR AU - Đoković, Marina AU - Peulić, Aleksandar AU - Filipović, Nenad PY - 2011 UR - https://gery.gef.bg.ac.rs/handle/123456789/410 AB - In this paper, we present a multiresolution scheme to detect stellate lesions in mammograms. Multiresolution analysis is used to analyze the images at different frequencies with different resolutions. First we removed the noise from mammograms using Multiresolution analysis and then we detected tumors. Then, using the Embedded Zerotree Wavelet (EZW) algorithm, we compressed denoising mammographic image and showed that by applying the algorithm to detect tumors in the compressed image we obtained the same results as in the case of non-compressed images. Experimental results obtained from the mammographic images of patients recorded in the Clinical Center in Kragujevac, show that using multiresolution algorithm can be detected tumors of different sizes. PB - Drunpp-Sarajevo, Sarajevo T2 - HealthMed T1 - Automatic identification breast cancer using multiresolution algorithm VL - 5 IS - 6 SP - 2051 EP - 2064 UR - https://hdl.handle.net/21.15107/rcub_gery_410 ER -
@article{ author = "Đoković, Marina and Peulić, Aleksandar and Filipović, Nenad", year = "2011", abstract = "In this paper, we present a multiresolution scheme to detect stellate lesions in mammograms. Multiresolution analysis is used to analyze the images at different frequencies with different resolutions. First we removed the noise from mammograms using Multiresolution analysis and then we detected tumors. Then, using the Embedded Zerotree Wavelet (EZW) algorithm, we compressed denoising mammographic image and showed that by applying the algorithm to detect tumors in the compressed image we obtained the same results as in the case of non-compressed images. Experimental results obtained from the mammographic images of patients recorded in the Clinical Center in Kragujevac, show that using multiresolution algorithm can be detected tumors of different sizes.", publisher = "Drunpp-Sarajevo, Sarajevo", journal = "HealthMed", title = "Automatic identification breast cancer using multiresolution algorithm", volume = "5", number = "6", pages = "2051-2064", url = "https://hdl.handle.net/21.15107/rcub_gery_410" }
Đoković, M., Peulić, A.,& Filipović, N.. (2011). Automatic identification breast cancer using multiresolution algorithm. in HealthMed Drunpp-Sarajevo, Sarajevo., 5(6), 2051-2064. https://hdl.handle.net/21.15107/rcub_gery_410
Đoković M, Peulić A, Filipović N. Automatic identification breast cancer using multiresolution algorithm. in HealthMed. 2011;5(6):2051-2064. https://hdl.handle.net/21.15107/rcub_gery_410 .
Đoković, Marina, Peulić, Aleksandar, Filipović, Nenad, "Automatic identification breast cancer using multiresolution algorithm" in HealthMed, 5, no. 6 (2011):2051-2064, https://hdl.handle.net/21.15107/rcub_gery_410 .