Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Senthilkumar, Krishnamurthy"'
Publikováno v:
Brazilian Archives of Biology and Technology, Vol 61, Iss 0 (2018)
ABSTRACT The objective of this work is to identify the malignant lung nodules accurately and early with less false positives. ‘Nodule’ is the 3mm to 30mm diameter size tissue clusters present inside the lung parenchyma region. Segmenting such a s
Externí odkaz:
https://doaj.org/article/cdd1068dcf5e406f98ba4ec6c840e291
Publikováno v:
International Journal of u- and e- Service, Science and Technology. 9:187-198
A Level Set Evolution with Morphology (LSEM) based segmentation algorithm is proposed in this work to segment all the possible lung nodules from a series of CT scan images. All the segmented nodule candidates were not cancerous in nature. Initially t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ba550b3756feb564f26532d2702acabd
https://doi.org/10.14257/ijunesst.2016.9.10.18
https://doi.org/10.14257/ijunesst.2016.9.10.18
Publikováno v:
Communications in Computer and Information Science ISBN: 9789811048586
RTIP2R
RTIP2R
The objective of this work is to identify the malignant lung nodules accurately and early with less false positives. In our work block histogram based auto center seed k-means clustering technique is used to segment all the possible nodule candidates
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::efc094a7079cddb77c0286caa8fcf102
https://doi.org/10.1007/978-981-10-4859-3_31
https://doi.org/10.1007/978-981-10-4859-3_31
Publikováno v:
Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine. 230(1)
The three-dimensional analysis on lung computed tomography scan was carried out in this study to detect the malignant lung nodules. An automatic three-dimensional segmentation algorithm proposed here efficiently segmented the tissue clusters (nodules
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a7f6e5854de9a846f235f4ad4035a36b
https://pubmed.ncbi.nlm.nih.gov/26721427
https://pubmed.ncbi.nlm.nih.gov/26721427
Autor:
Periyannan, Mani, Selvaraju, Mani, Gopikrishnan, Duraisamy, Senthilkumar, Krishnamurthy, Varudharajan, Venkatraman, Ravikumar, Kaliannan
Publikováno v:
Indian Journal of Veterinary Sciences & Biotechnology; Jul-Sep2021, Vol. 17 Issue 3, p105-107, 3p
Publikováno v:
International Journal of Biomedical Engineering and Technology. 24:53
A quantitative model is developed in this work to predict the lung nodules which have the potential to grow in future. An Auto Cluster Seed K-means Morphological segmentation (ACSKMM) algorithm was implemented in this work to segment all the possible
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::99cfaee663fb14ce4f8fc1f22b18038e
https://doi.org/10.1504/ijbet.2017.083818
https://doi.org/10.1504/ijbet.2017.083818
Autor:
Periyannan, Mani, Selvaraju, Mani, Senthilkumar, Krishnamurthy, Varudharajan, Venkatraman, Prakash, Subramanian, Palanisamy, Mahakrishnan
Publikováno v:
Indian Journal of Veterinary Sciences & Biotechnology; Jul-Sep2021, Vol. 17 Issue 3, p110-111, 2p
Publikováno v:
Proceedings of the Institution of Mechanical Engineers -- Part H -- Journal of Engineering in Medicine (Sage Publications, Ltd.); Jan2016, Vol. 230 Issue 1, p58-70, 13p
This book constitutes the refereed proceedings of the First International Conference on Recent Trends in Image Processing and Pattern Recognition, RTIP2R 2016, held in Bidar, Karnataka, India, in December 2016. The 39 revised full papers presented we