Selection of a Stopping Criterion for Anisotropic Diffusion Filtering in Ultrasound Images
Ultrasound imaging is a safe and cost-effective diagnostic tool, but the quality of the images is affected by speckle noise and artifacts. Anisotropic diffusion filters can be used to reduce noise and preserve the edges in the image. However, this technique is very sensitive to the number of iterati...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2019
- Institución:
- Universidad Tecnológica de Bolívar
- Repositorio:
- Repositorio Institucional UTB
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.utb.edu.co:20.500.12585/9148
- Acceso en línea:
- https://hdl.handle.net/20.500.12585/9148
- Palabra clave:
- Anisotropic diffusion filtering
Speckle reduction
Stopping criterion
Ultrasound image enhancement
Cost effectiveness
Diffusion
Image enhancement
Optical anisotropy
Speckle
Ultrasonic imaging
Vision
Anisotropic diffusion filtering
Anisotropic diffusion filters
Number of iterations
Speckle reduction
Stopping criteria
Ultrasound image enhancements
Ultrasound images
Ultrasound imaging
Image denoising
- Rights
- restrictedAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
| id |
UTB2_6f83b2bef3e089d574f646f945b4b2c7 |
|---|---|
| oai_identifier_str |
oai:repositorio.utb.edu.co:20.500.12585/9148 |
| network_acronym_str |
UTB2 |
| network_name_str |
Repositorio Institucional UTB |
| repository_id_str |
|
| dc.title.none.fl_str_mv |
Selection of a Stopping Criterion for Anisotropic Diffusion Filtering in Ultrasound Images |
| title |
Selection of a Stopping Criterion for Anisotropic Diffusion Filtering in Ultrasound Images |
| spellingShingle |
Selection of a Stopping Criterion for Anisotropic Diffusion Filtering in Ultrasound Images Anisotropic diffusion filtering Speckle reduction Stopping criterion Ultrasound image enhancement Cost effectiveness Diffusion Image enhancement Optical anisotropy Speckle Ultrasonic imaging Vision Anisotropic diffusion filtering Anisotropic diffusion filters Number of iterations Speckle reduction Stopping criteria Ultrasound image enhancements Ultrasound images Ultrasound imaging Image denoising |
| title_short |
Selection of a Stopping Criterion for Anisotropic Diffusion Filtering in Ultrasound Images |
| title_full |
Selection of a Stopping Criterion for Anisotropic Diffusion Filtering in Ultrasound Images |
| title_fullStr |
Selection of a Stopping Criterion for Anisotropic Diffusion Filtering in Ultrasound Images |
| title_full_unstemmed |
Selection of a Stopping Criterion for Anisotropic Diffusion Filtering in Ultrasound Images |
| title_sort |
Selection of a Stopping Criterion for Anisotropic Diffusion Filtering in Ultrasound Images |
| dc.subject.keywords.none.fl_str_mv |
Anisotropic diffusion filtering Speckle reduction Stopping criterion Ultrasound image enhancement Cost effectiveness Diffusion Image enhancement Optical anisotropy Speckle Ultrasonic imaging Vision Anisotropic diffusion filtering Anisotropic diffusion filters Number of iterations Speckle reduction Stopping criteria Ultrasound image enhancements Ultrasound images Ultrasound imaging Image denoising |
| topic |
Anisotropic diffusion filtering Speckle reduction Stopping criterion Ultrasound image enhancement Cost effectiveness Diffusion Image enhancement Optical anisotropy Speckle Ultrasonic imaging Vision Anisotropic diffusion filtering Anisotropic diffusion filters Number of iterations Speckle reduction Stopping criteria Ultrasound image enhancements Ultrasound images Ultrasound imaging Image denoising |
| description |
Ultrasound imaging is a safe and cost-effective diagnostic tool, but the quality of the images is affected by speckle noise and artifacts. Anisotropic diffusion filters can be used to reduce noise and preserve the edges in the image. However, this technique is very sensitive to the number of iterations selected. This paper proposes a stopping criterion for effective noise removal without blurring the edges, based on the relative variance between the estimated denoised image and the original one. Different quality metrics were evaluated in 25 test images. The results suggest that the proposed stopping criterion can be implemented efficiently and aids in the process of automation of the filter. © 2019 IEEE. |
| publishDate |
2019 |
| dc.date.issued.none.fl_str_mv |
2019 |
| dc.date.accessioned.none.fl_str_mv |
2020-03-26T16:33:03Z |
| dc.date.available.none.fl_str_mv |
2020-03-26T16:33:03Z |
| dc.type.coarversion.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_c94f |
| dc.type.driver.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
| dc.type.hasversion.none.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
| dc.type.spa.none.fl_str_mv |
Conferencia |
| status_str |
publishedVersion |
| dc.identifier.citation.none.fl_str_mv |
2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings |
| dc.identifier.isbn.none.fl_str_mv |
9781728114910 |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12585/9148 |
| dc.identifier.doi.none.fl_str_mv |
10.1109/STSIVA.2019.8730287 |
| dc.identifier.instname.none.fl_str_mv |
Universidad Tecnológica de Bolívar |
| dc.identifier.reponame.none.fl_str_mv |
Repositorio UTB |
| dc.identifier.orcid.none.fl_str_mv |
57209541901 57210822856 |
| identifier_str_mv |
2019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings 9781728114910 10.1109/STSIVA.2019.8730287 Universidad Tecnológica de Bolívar Repositorio UTB 57209541901 57210822856 |
| url |
https://hdl.handle.net/20.500.12585/9148 |
| dc.language.iso.none.fl_str_mv |
eng |
| language |
eng |
| dc.relation.conferencedate.none.fl_str_mv |
24 April 2019 through 26 April 2019 |
| dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_16ec |
| dc.rights.uri.none.fl_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ |
| dc.rights.accessrights.none.fl_str_mv |
info:eu-repo/semantics/restrictedAccess |
| dc.rights.cc.none.fl_str_mv |
Atribución-NoComercial 4.0 Internacional |
| rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-nd/4.0/ Atribución-NoComercial 4.0 Internacional http://purl.org/coar/access_right/c_16ec |
| eu_rights_str_mv |
restrictedAccess |
| dc.format.medium.none.fl_str_mv |
Recurso electrónico |
| dc.format.mimetype.none.fl_str_mv |
application/pdf |
| dc.publisher.none.fl_str_mv |
Institute of Electrical and Electronics Engineers Inc. |
| publisher.none.fl_str_mv |
Institute of Electrical and Electronics Engineers Inc. |
| dc.source.none.fl_str_mv |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068081454&doi=10.1109%2fSTSIVA.2019.8730287&partnerID=40&md5=547d371e28c0c01ef46a5d37bd2fb3a8 Scopus2-s2.0-85068081454 |
| institution |
Universidad Tecnológica de Bolívar |
| dc.source.event.none.fl_str_mv |
22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 |
| bitstream.url.fl_str_mv |
https://repositorio.utb.edu.co/bitstream/20.500.12585/9148/1/MiniProdInv.png |
| bitstream.checksum.fl_str_mv |
0cb0f101a8d16897fb46fc914d3d7043 |
| bitstream.checksumAlgorithm.fl_str_mv |
MD5 |
| repository.name.fl_str_mv |
Repositorio Institucional UTB |
| repository.mail.fl_str_mv |
repositorioutb@utb.edu.co |
| _version_ |
1814021604409081856 |
| spelling |
2020-03-26T16:33:03Z2020-03-26T16:33:03Z20192019 22nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019 - Conference Proceedings9781728114910https://hdl.handle.net/20.500.12585/914810.1109/STSIVA.2019.8730287Universidad Tecnológica de BolívarRepositorio UTB5720954190157210822856Ultrasound imaging is a safe and cost-effective diagnostic tool, but the quality of the images is affected by speckle noise and artifacts. Anisotropic diffusion filters can be used to reduce noise and preserve the edges in the image. However, this technique is very sensitive to the number of iterations selected. This paper proposes a stopping criterion for effective noise removal without blurring the edges, based on the relative variance between the estimated denoised image and the original one. Different quality metrics were evaluated in 25 test images. The results suggest that the proposed stopping criterion can be implemented efficiently and aids in the process of automation of the filter. © 2019 IEEE.IEEE Colombia Section;IEEE Signal Processing Society Colombia Chapter;Universidad Industrial de SantanderRecurso electrónicoapplication/pdfengInstitute of Electrical and Electronics Engineers Inc.http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/restrictedAccessAtribución-NoComercial 4.0 Internacionalhttp://purl.org/coar/access_right/c_16echttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85068081454&doi=10.1109%2fSTSIVA.2019.8730287&partnerID=40&md5=547d371e28c0c01ef46a5d37bd2fb3a8Scopus2-s2.0-8506808145422nd Symposium on Image, Signal Processing and Artificial Vision, STSIVA 2019Selection of a Stopping Criterion for Anisotropic Diffusion Filtering in Ultrasound Imagesinfo:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionConferenciahttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_c94fAnisotropic diffusion filteringSpeckle reductionStopping criterionUltrasound image enhancementCost effectivenessDiffusionImage enhancementOptical anisotropySpeckleUltrasonic imagingVisionAnisotropic diffusion filteringAnisotropic diffusion filtersNumber of iterationsSpeckle reductionStopping criteriaUltrasound image enhancementsUltrasound imagesUltrasound imagingImage denoising24 April 2019 through 26 April 2019Guillen J.E.I.Contreras Ortiz, Sonia Helena(2018) Nacimiento y Defunciones 2016-2017pr, p. 12. , DANE, Estadisticas vitales. DANE, mar(2018) Global Health Estimates 2016: Dalys by Cause Globally, 2016 and 2000., , World Health Organization, JunePerona, P., Malik, J., Scale-Space and edge detection using anisotropic diffusion (1990) IEEE Transactions on Pattern Analysis and Machine Intelligence, 12 (7), pp. 629-639. , JulyYu, Y., Acton, S., Speckle reducing Anisotropic diffusion (2002) IEEE Transactions on Image Processing, 11 (1260-1270), pp. 629-639. , NovemberAbd-Elmoniem, K.Z., Kadah, Y., Real-time speckle reduction and coherence enhancement in ultrasound imaging via nonlinear anisotropic diffusion (2002) IEEE Transactions on Biomedical Engineering, 49 (9), pp. 997-1014. , SeptMittal, D., Kumar, V., Saxena, S.C., Khandelwal, N., Kalra, N., Enhancement of the ultrasound images by modified anisotropic diffusion method (2010) Medical & Biological Engineering & Computing, 48 (12), pp. 1281-1291Xu, J., Jia, Y., Shi, Z., Pang, K., An improved anisotropic diffusion filter with semi-adaptive threshold for edge preservation (2016) Signal Processing, 119, pp. 80-91Garg, A., Khandelwal, V., Combination of spatial domain filters for speckle noise reduction in ultrasound medical images (2018) Advances in Electrical and Electronic Engineering, 15 (5), pp. 857-865Weickert, J., Coherence-enhancing diffusion of colour images1 (1999) Image and Vision Computing, 17 (3-4), pp. 201-212Mrázek, P., Navara, M., Selection of optimal stopping time for nonlinear diffusion filtering (2003) International Journal of Computer Vision, 52 (2-3), pp. 189-203Tsiotsios, C., Petrou, M., On the choice of the parameters for anisotropic diffusion in image processing (2013) Pattern Recognition, 46 (5), pp. 1369-1381Fernández, J.-J., Li, S., An improved algorithm for anisotropic nonlinear diffusion for denoising cryo-tomograms (2003) Journal of Structural Biology, 144 (1-2), pp. 152-161Giraldo-Guzmán, J., Porto-Solano, O., Cadena-Bonfanti, A., Contreras-Ortiz, S.H., Speckle reduction in echocardiography by temporal compounding and anisotropic diffusion filtering (2015) 10th International Symposium on Medical Information Processing and Analysis, 9287, p. 92871F. , International Society for Optics and PhotonicsContreras-Ortiz, S.H., Fox, M.D., Hexagonal filters for ultrasound images (2014) Journal of Electronic Imaging, 23 (4), p. 043022Burckhardt, C.B., Speckle in ultrasound b-mode scans (1978) Sonics and Ultrasonics, IEEE Transactions on, 25 (1), pp. 1-6Wang, Z., Bovik, A.C., A universal image quality index (2002) IEEE Signal Processing Letters, 9 (3), pp. 81-84Jensen, J.A., Field: A program for simulating ultrasound systems (1997) Medical & Biological Engineering & Computing, 34 (1), pp. 351-353http://purl.org/coar/resource_type/c_c94fTHUMBNAILMiniProdInv.pngMiniProdInv.pngimage/png23941https://repositorio.utb.edu.co/bitstream/20.500.12585/9148/1/MiniProdInv.png0cb0f101a8d16897fb46fc914d3d7043MD5120.500.12585/9148oai:repositorio.utb.edu.co:20.500.12585/91482023-05-25 15:54:05.714Repositorio Institucional UTBrepositorioutb@utb.edu.co |