Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Sunita Agarwala"'
Autor:
Sunita Agarwala, Kumar, Abhishek, Dhara, Ashis Kumar, Thakur, Sumitra Basu, Sadhu, Anup, Nandi, Debashis
Publikováno v:
Pattern Recognition and Image Analysis
In this paper, automated detection of interstitial lung disease patterns in high resolution computed tomography images is achieved by developing a faster region-based convolutional network based detector with GoogLeNet as a backbone. GoogLeNet is sim
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ff5ddfae6f47c268e3ac0eff27c3170b
https://doi.org/10.1134/s1054661821040027
https://doi.org/10.1134/s1054661821040027
Publikováno v:
2022 IEEE Region 10 Symposium (TENSYMP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::83728dc748dbd485f67d13b5a3283086
https://doi.org/10.1109/tensymp54529.2022.9864546
https://doi.org/10.1109/tensymp54529.2022.9864546
Autor:
M. Kale, A. Kumar Dhara, Sunita Agarwala, D. Kumar, Anirudh Kumar, Debashis Nandi, S. Basu Thakur, Anup K. Sadhu, R. Swaroop
Publikováno v:
Clinical Radiology. 75:481.e1-481.e8
AIM To develop a screening tool for the detection of interstitial lung disease (ILD) patterns using a deep-learning method. MATERIALS AND METHODS A fully convolutional network was used for semantic segmentation of several ILD patterns. Improved segme
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d752df00f05d8a139cce779f8cf81fdb
https://doi.org/10.1016/j.crad.2020.01.010
https://doi.org/10.1016/j.crad.2020.01.010
Autor:
Sunita Agarwala, Debashis Nandi, Abhishek Kumar, Niranjan Khandelwal, Sudipta Mukhopadhyay, Mandeep Garg, Naveen Kalra, Ashis Kumar Dhara
Publikováno v:
Medical Imaging: Computer-Aided Diagnosis
Lung field segmentation is a prerequisite step for the development of a computer-aided diagnosis system for interstitial lung diseases observed in chest HRCT images. Conventional methods of lung field segmentation rely on a large gray value contrast
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d693007040b39cb9f6e84288153531c9
https://doi.org/10.1117/12.2293503
https://doi.org/10.1117/12.2293503
Autor:
Sumitra Basu Thakur, Sunita Agarwala, Anup K. Sadhu, Ashis Kumar Dhara, Ashok Kumar Bhadra, Abhishek Kumar, Debashis Nandi
Publikováno v:
Communications in Computer and Information Science ISBN: 9783319959207
MIUA
MIUA
Lung field segmentation is the first step towards the development of any computer aided diagnosis (CAD) system for interstitial lung diseases (ILD) observed in chest high resolution computed tomography (HRCT) images. If the segmentation is not done e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ac6de063f64afebd0bcd03f0828ffdeb
https://doi.org/10.1007/978-3-319-95921-4_2
https://doi.org/10.1007/978-3-319-95921-4_2
Autor:
Ashis Kumar Dhara, Anup K. Sadhu, Sumitra Basu Thakur, Ashok Kumar Bhadra, Abhishek Kumar, Debashis Nandi, Sunita Agarwala
Publikováno v:
Communications in Computer and Information Science ISBN: 9783319959207
MIUA
MIUA
Segmentation is a preliminary step towards the development of automated computer aided diagnosis system (CAD). The system accuracy and efficiency primarily depend on the accurate segmentation result. Effective lung field segmentation is major challen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::37b50cca29bf27d141be0b92713d3b63
https://doi.org/10.1007/978-3-319-95921-4_10
https://doi.org/10.1007/978-3-319-95921-4_10
Autor:
Debashis Nandi, Abhishek Kumar, Sumitra Basu Thakur Anup Sadhu, Ashis Kumar Dhara, Ashok Kumar Bhadra, Sunita Agarwala
Publikováno v:
TENCON 2017 - 2017 IEEE Region 10 Conference.
Lung field segmentation is a prerequisite for the development of automated computer aided diagnosis of interstitial lung diseases from chest high resolution computed tomography (HRCT) images. The traditional threshold-based or region growing methods
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5a172e58a14b3e041544c78377ad6eb6
https://doi.org/10.1109/tencon.2017.8228285
https://doi.org/10.1109/tencon.2017.8228285