Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Arunabha S. Roy"'
Publikováno v:
Medical Physics. 33:1133-1140
We present a number of approaches based on the radial gradient index (RGI) to achieve false-positive reduction in automated CT lung nodule detection. A database of 38 cases was used that contained a total of 82 lung nodules. For each CT section, a co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ebc23351079a576d8955b247801017d8
https://doi.org/10.1118/1.2178450
https://doi.org/10.1118/1.2178450
Autor:
Shusuke Sone, Michael B. Altman, Feng Li, Arunabha S. Roy, Kunio Doi, Joel R. Wilkie, Samuel G. Armato
Publikováno v:
Medical Physics. 30:1188-1197
We have evaluated the performance of an automated classifier applied to the task of differentiating malignant and benign lung nodules in low-dose helical computed tomography (CT) scans acquired as part of a lung cancer screening program. The nodules
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::70e81996b154d41da8e9790b48d64695
https://doi.org/10.1118/1.1573210
https://doi.org/10.1118/1.1573210
Publikováno v:
Medical Imaging: Image Processing
Robust point matching (RPM) jointly estimates correspondences and non-rigid warps between unstructured point-clouds. RPM does not, however, utilize information of the topological structure or group memberships of the data it is matching. In numerous
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ddaab66f495ab504c8fa358696b5b259
https://doi.org/10.1117/12.844226
https://doi.org/10.1117/12.844226
Publikováno v:
ISBI
Robust point matching (RPM) simultaneously estimates correspondences and non-rigid warps between unstructured point-sets. While RPM is robust to outliers in the target (fixed) point-set, its performance degrades when the template (moving) point-set c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9962ee063ea2417c98000623d4172078
https://doi.org/10.1109/isbi.2010.5490331
https://doi.org/10.1109/isbi.2010.5490331
Autor:
Ravindra Mohan Manjeshwar, Uday Patil, Arunabha S. Roy, Kris Thielemans, G.V. Saradhi, Girishankar Gopalakrishnan, Rakesh Mullick
Publikováno v:
ISBI
This paper proposes a novel framework for tumor detection in Positron Emission Tomography (PET) images. A set of 8 second-order texture features obtained from the gray level co-occurrence matrix (GLCM) across 26 offsets, together with uptake value wa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::db2c017209057d3e022ec275b6354751
https://doi.org/10.1109/isbi.2009.5192992
https://doi.org/10.1109/isbi.2009.5192992
Publikováno v:
Medical Imaging: Image Processing
Automated labeling of the bronchial tree is essential for localization of airway related diseases (e.g. chronic bronchitis) and is also a useful precursor to lung-lobe labeling. We describe an automated method for registration-based labeling of a bro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7eb925a3af24b33d39bbcb3eb74553bf
https://doi.org/10.1117/12.812496
https://doi.org/10.1117/12.812496
Publikováno v:
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007 ISBN: 9783540757566
MICCAI (1)
MICCAI (1)
There exists a large body of literature on shape matching and registration in medical image analysis. However, most of the previous work is focused on matching particular sets of features--point-sets, lines, curves and surfaces. In this work, we fors
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fb2304c9b16df13d615f7552a73c6d31
https://doi.org/10.1007/978-3-540-75757-3_114
https://doi.org/10.1007/978-3-540-75757-3_114
Publikováno v:
Medical physics. 33(4)
We present a number of approaches based on the radial gradient index (RGI) to achieve false-positive reduction in automated CT lung nodule detection. A database of 38 cases was used that contained a total of 82 lung nodules. For each CT section, a co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::fb39f08dcb8be00a99a5fe7c344d0bc2
https://pubmed.ncbi.nlm.nih.gov/16696491
https://pubmed.ncbi.nlm.nih.gov/16696491
Autor:
Heber MacMahon, Michael B. Altman, Arunabha S. Roy, Samuel G. Armato, Feng Li, Shusuke Sone, Kunio Doi
Publikováno v:
Academic radiology. 12(3)
Rationale and Objectives. The purpose of this study was to evaluate the performance of a fully automated lung nodule detection method in a large database of low-dose computed tomography (CT) scans from a lung cancer screening program. Because nodules
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::12d040bf29eb9200202daa05087d97ac
https://pubmed.ncbi.nlm.nih.gov/15766694
https://pubmed.ncbi.nlm.nih.gov/15766694
Publikováno v:
Medical Imaging: Image Processing
Blood vessel segmentation in volumetric data is a necessary prerequisite in various medical imaging applications. Specifically, when considering the application of automatic lung nodule detection in thoracic CT scans, segmented blood vessels can be u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::acd6485e6ccddb02345e582b3f432d15
https://doi.org/10.1117/12.533175
https://doi.org/10.1117/12.533175