Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Lipismita Panigrahi"'
Publikováno v:
IET Computer Vision, Vol 12, Iss 8, Pp 1067-1077 (2018)
Automated segmentation of tumors in breast ultrasound (US) images is challenging due to poor image quality, presence of speckle noise, shadowing effects and acoustic enhancement. This paper improves the multi‐scale Gaussian kernel induced fuzzy C
Externí odkaz:
https://doaj.org/article/4fa5b0763b7a41dfa06c3d21fa5e3f2d
Publikováno v:
2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1b5a5d6818e2bb5d44a182e1440847c6
https://doi.org/10.1109/otcon56053.2023.10113957
https://doi.org/10.1109/otcon56053.2023.10113957
Publikováno v:
2022 OPJU International Technology Conference on Emerging Technologies for Sustainable Development (OTCON).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e7252813748964c9be0576d110b92620
https://doi.org/10.1109/otcon56053.2023.10114045
https://doi.org/10.1109/otcon56053.2023.10114045
Publikováno v:
IETE Journal of Research. 68:935-946
Feature extraction and classification plays a crucial role in the automated analysis of breast ultrasound (BUS) images. Due to varying sonographic characteristics of benign and malignant lesions, t...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::85b54c4f78fc3807ab435387b4337799
https://doi.org/10.1080/03772063.2019.1627918
https://doi.org/10.1080/03772063.2019.1627918
Publikováno v:
Expert Systems with Applications. 115:486-498
Ultrasound imaging is most popular technique used for breast cancer screening. Lesion segmentation is challenging step in characterization of breast ultrasound (US) based Computer Aided Diagnosis (CAD) systems due to presence of speckle noise, shadow
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c17416d51394e7e92f42cc7769626b01
https://doi.org/10.1016/j.eswa.2018.08.013
https://doi.org/10.1016/j.eswa.2018.08.013
Publikováno v:
IET Computer Vision. 12:1067-1077
Automated segmentation of tumors in breast ultrasound (US) images is challenging due to poor image quality, presence of speckle noise, shadowing effects and acoustic enhancement. This paper improves the multi-scale Gaussian kernel induced fuzzy C-mea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ea9b366e38f70748432a2a252892bd1e
https://doi.org/10.1049/iet-cvi.2018.5332
https://doi.org/10.1049/iet-cvi.2018.5332
The healthcare industry is predominantly moving towards affordable, accessible, and quality health care. All organizations are striving to build communication compatibility among the wide range of devices that have operated independently. Recent deve
Publikováno v:
Expert Systems with Applications. 90:209-223
With advancements in machine learning algorithms and computer aided diagnostic (CAD) systems, the performance of automated analysis of radiological images has improved substantially in recent times. However, the lack of integration between the radiol
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c6e4b474924507b9b10d2b14893c51a1
https://doi.org/10.1016/j.eswa.2017.08.020
https://doi.org/10.1016/j.eswa.2017.08.020
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9789811073854
Automatic boundary detection is a challenging and one of the important issues in medical imaging. Contouring breast tumor lesions automatically may avail physicians for correct and faster diseases diagnoses. The ultrasound images are noisy, and bound
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ffb07e1fda4c1ca370f7a520e96c2a56
https://doi.org/10.1007/978-981-10-7386-1_61
https://doi.org/10.1007/978-981-10-7386-1_61
An enhancement in automatic seed selection in breast cancer ultrasound images using texture features
Publikováno v:
ICACCI
Automatic seed selection is an important and crucial step toward the boundary detection in ultrasound B-scan images. This paper focuses on a methodological framework that can automatically detect a seed point of an ultrasound image by using texture f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0f750845d36a03df815a62138df62313
https://doi.org/10.1109/icacci.2016.7732191
https://doi.org/10.1109/icacci.2016.7732191