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Dhara, Ashis Kumar
Publications (6 of 6) Show all publications
Mehre, S. A., Dhara, A. K., Garg, M., Kalra, N., Khandelwal, N. & Mukhopadhyay, S. (2019). Content-Based Image Retrieval System for Pulmonary Nodules Using Optimal Feature Sets and Class Membership-Based Retrieval. Journal of digital imaging, 32, 362-385
Open this publication in new window or tab >>Content-Based Image Retrieval System for Pulmonary Nodules Using Optimal Feature Sets and Class Membership-Based Retrieval
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2019 (English)In: Journal of digital imaging, ISSN 0897-1889, E-ISSN 1618-727X, Vol. 32, p. 362-385Article in journal (Refereed) Published
National Category
Medical Image Processing
Identifiers
urn:nbn:se:uu:diva-385003 (URN)10.1007/s10278-018-0136-1 (DOI)000466896500003 ()30361935 (PubMedID)
Available from: 2018-10-25 Created: 2019-06-11 Last updated: 2019-06-13Bibliographically approved
Patra, H. K., Azharuddin, M., Islam, M. M., Papapavlou, G., Deb, S., Osterrieth, J., . . . Slater, N. K. H. (2019). Rational nanotoolbox with theranostic potential for medicated pro-regenerative corneal implants. Advanced Functional Materials, 29(38), Article ID 1903760.
Open this publication in new window or tab >>Rational nanotoolbox with theranostic potential for medicated pro-regenerative corneal implants
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2019 (English)In: Advanced Functional Materials, ISSN 1616-301X, E-ISSN 1616-3028, Vol. 29, no 38, article id 1903760Article in journal (Refereed) Published
National Category
Medical Image Processing
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-396138 (URN)10.1002/adfm.201903760 (DOI)000476281800001 ()
Available from: 2019-07-15 Created: 2019-11-04 Last updated: 2019-11-04Bibliographically approved
Dhara, A. K., Arids, E., Fahlström, M., Wikström, J., Larsson, E.-M. & Strand, R. (2018). Interactive segmentation of glioblastoma for post-surgical treatment follow-up. In: Proc. 24th International Conference on Pattern Recognition: . Paper presented at ICPR 2018, August 20–24, Beijing, China (pp. 1199-1204). IEEE
Open this publication in new window or tab >>Interactive segmentation of glioblastoma for post-surgical treatment follow-up
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2018 (English)In: Proc. 24th International Conference on Pattern Recognition, IEEE, 2018, p. 1199-1204Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
IEEE, 2018
National Category
Medical Image Processing
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-368290 (URN)10.1109/ICPR.2018.8545105 (DOI)000455146801036 ()978-1-5386-3788-3 (ISBN)
Conference
ICPR 2018, August 20–24, Beijing, China
Note

Best paper award

Available from: 2018-12-03 Created: 2018-12-03 Last updated: 2019-02-21Bibliographically approved
Kumar, A., Agarwala, S., Dhara, A. K., Mukhopadhyay, S., Nandi, D., Garg, M., . . . Kalra, N. (2018). Localization of lung fields in HRCT images using a deep convolution neural network. In: Medical Imaging 2018: Computer-Aided Diagnosis. Paper presented at SPIE Medical Imaging 2018, February 12–15, Houston, TX (pp. 1057535:1-8). Bellingham, WA, Article ID 1057535.
Open this publication in new window or tab >>Localization of lung fields in HRCT images using a deep convolution neural network
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2018 (English)In: Medical Imaging 2018: Computer-Aided Diagnosis, Bellingham, WA, 2018, p. 1057535:1-8, article id 1057535Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Bellingham, WA: , 2018
Series
Proc. SPIE ; 10575
National Category
Medical Image Processing
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-358432 (URN)10.1117/12.2293503 (DOI)000432546900109 ()978-1-5106-1640-0 (ISBN)
Conference
SPIE Medical Imaging 2018, February 12–15, Houston, TX
Available from: 2018-02-27 Created: 2018-08-30 Last updated: 2018-08-31Bibliographically approved
Dhara, A. K., Ayyalasomayajula, K. R., Arvids, E., Fahlström, M., Wikström, J., Larsson, E.-M. & Strand, R. (2018). Segmentation of Post-operative Glioblastoma in MRI by U-Net with Patient-specific Interactive Refinement. In: Proceedings, Brain Lesion (BrainLes) workshop: . Paper presented at 21st INTERNATIONAL CONFERENCE ON MEDICAL IMAGE COMPUTING & COMPUTER ASSISTED INTERVENTION, September 16-20, 2018, Granada, Spain.
Open this publication in new window or tab >>Segmentation of Post-operative Glioblastoma in MRI by U-Net with Patient-specific Interactive Refinement
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2018 (English)In: Proceedings, Brain Lesion (BrainLes) workshop, 2018Conference paper, Published paper (Refereed)
Abstract [en]

Accurate volumetric change estimation of glioblastoma is very important for post-surgical treatment follow-up. In this paper, an interactive segmentation method was developed and evaluated with the aim to guide volumetric estimation of glioblastoma. U-Net based fully convolutional network is used for initial segmentation of glioblastoma from post contrast MR images. The max flow algorithm is applied on the probability map of U-Net to update the initial segmentation and the result is displayed to the user for interactive refinement. Network update is performed based on the corrected contour by considering patient specific learning to deal with large context variations among dierent images. The proposed method is evaluated on a clinical MR image databas eof 15 glioblastoma patients with longitudinal scan data. The experimental results depict an improvement of segmentation performance due to patient specific fine-tuning. The proposed method is computationally fast and efficient as compared to state-of-the-art interactive segmentation tools. This tool could be useful for post-surgical treatment follow-upwith minimal user intervention.

National Category
Medical Image Processing
Identifiers
urn:nbn:se:uu:diva-366550 (URN)
Conference
21st INTERNATIONAL CONFERENCE ON MEDICAL IMAGE COMPUTING & COMPUTER ASSISTED INTERVENTION, September 16-20, 2018, Granada, Spain
Funder
Swedish Research Council, 2014-6199Vinnova, 2017-02447
Note

Extended versions of all accepted papers will be published as LCNS proceedings by Springer-Verlag. http://www.brainlesion-workshop.org/

Available from: 2018-11-21 Created: 2018-11-21 Last updated: 2019-03-14Bibliographically approved
Agarwala, S., Nandi, D., Kumar, A., Dhara, A. K., Thakur, S. B., Sadhu, A. & Bhadra, A. K. (2017). Automated segmentation of lung field in HRCT images using active shape model. In: Proc. 37th Region 10 Conference: . Paper presented at TENCON 2017, November 5–8, Penang, Malaysia (pp. 2516-2520). IEEE
Open this publication in new window or tab >>Automated segmentation of lung field in HRCT images using active shape model
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2017 (English)In: Proc. 37th Region 10 Conference, IEEE, 2017, p. 2516-2520Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
IEEE, 2017
National Category
Medical Image Processing
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-352949 (URN)10.1109/TENCON.2017.8228285 (DOI)000426330002104 ()978-1-5090-1134-6 (ISBN)
Conference
TENCON 2017, November 5–8, Penang, Malaysia
Available from: 2017-12-21 Created: 2018-06-12 Last updated: 2018-06-13Bibliographically approved
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