Zobrazeno 1 - 10
of 67
pro vyhledávání: '"Ganapathy Krishnamurthi"'
Autor:
Minmini Selvam, Anupama Chandrasekharan, Abjasree Sadanandan, Vikas K. Anand, Sidharth Ramesh, Arunan Murali, Ganapathy Krishnamurthi
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-12 (2024)
Abstract This observational study investigated the potential of radiomics as a non-invasive adjunct to CT in distinguishing COVID-19 lung nodules from other benign and malignant lung nodules. Lesion segmentation, feature extraction, and machine learn
Externí odkaz:
https://doaj.org/article/77915263635743b89d40dfe8fe3bf48c
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-17 (2024)
Abstract Effective training of deep image segmentation models is challenging due to the need for abundant, high-quality annotations. To facilitate image annotation, we introduce Physics Informed Contour Selection (PICS)—an interpretable, physics-in
Externí odkaz:
https://doaj.org/article/6f58f5b09044439cb6b89788748d716b
Autor:
Minmini Selvam, Anupama Chandrasekharan, Abjasree Sadanandan, Vikas Kumar Anand, Arunan Murali, Ganapathy Krishnamurthi
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-14 (2023)
Abstract In an observational study conducted from 2016 to 2021, we assessed the utility of radiomics in differentiating between benign and malignant lung nodules detected on computed tomography (CT) scans. Patients in whom a final diagnosis regarding
Externí odkaz:
https://doaj.org/article/e2433ffbf03d4287a6a207e2839c1a11
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-10 (2022)
Abstract The rapid progress in image-to-image translation methods using deep neural networks has led to advancements in the generation of synthetic CT (sCT) in MR-only radiotherapy workflow. Replacement of CT with MR reduces unnecessary radiation exp
Externí odkaz:
https://doaj.org/article/32e2067024f54f6383c91fc13b7d804d
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
Abstract Histopathology tissue analysis is considered the gold standard in cancer diagnosis and prognosis. Whole-slide imaging (WSI), i.e., the scanning and digitization of entire histology slides, are now being adopted across the world in pathology
Externí odkaz:
https://doaj.org/article/41e5df922c4a416987a654bf7f568fc6
Publikováno v:
PLoS ONE, Vol 17, Iss 2, p e0262913 (2022)
We present the design and characterization of an X-ray imaging system consisting of an off-the-shelf CMOS sensor optically coupled to a CsI scintillator. The camera can perform both high-resolution and functional cardiac imaging. High-resolution 3D i
Externí odkaz:
https://doaj.org/article/a29e59d1d15746ce978742e955c27b6d
Publikováno v:
Frontiers in Computational Neuroscience, Vol 15 (2021)
Externí odkaz:
https://doaj.org/article/e9255fe12a494d77aec180672f74fe8b
Publikováno v:
Frontiers in Computational Neuroscience, Vol 14 (2020)
The accurate automatic segmentation of gliomas and its intra-tumoral structures is important not only for treatment planning but also for follow-up evaluations. Several methods based on 2D and 3D Deep Neural Networks (DNN) have been developed to segm
Externí odkaz:
https://doaj.org/article/cf7ecc8787ac4f1d88c8431a4a7c2075
Autor:
Tahsin Kurc, Spyridon Bakas, Xuhua Ren, Aditya Bagari, Alexandre Momeni, Yue Huang, Lichi Zhang, Ashish Kumar, Marc Thibault, Qi Qi, Qian Wang, Avinash Kori, Olivier Gevaert, Yunlong Zhang, Dinggang Shen, Mahendra Khened, Xinghao Ding, Ganapathy Krishnamurthi, Jayashree Kalpathy-Cramer, James Davis, Tianhao Zhao, Rajarsi Gupta, Joel Saltz, Keyvan Farahani
Publikováno v:
Frontiers in Neuroscience, Vol 14 (2020)
Biomedical imaging Is an important source of information in cancer research. Characterizations of cancer morphology at onset, progression, and in response to treatment provide complementary information to that gleaned from genomics and clinical data.
Externí odkaz:
https://doaj.org/article/0c2926c1e89042aeb25319dba419c252
Publikováno v:
BMC Medical Imaging, Vol 17, Iss 1, Pp 1-13 (2017)
Abstract Background Tagged Magnetic Resonance (tMR) imaging is a powerful technique for determining cardiovascular abnormalities. One of the reasons for tMR not being used in routine clinical practice is the lack of easy-to-use tools for image analys
Externí odkaz:
https://doaj.org/article/fbaeeb47c35c4ac9b11a06bde7712dc3