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2020 – today
- 2024
[j6]Syedsafi Shajahan, Padmanaban Sriramakrishnan, Kalaiselvi Thiruvenkadam
:
RIBM3DU-Net: Glioma tumour substructures segmentation in magnetic resonance images using residual-inception block with modified 3D U-Net architecture. Int. J. Imaging Syst. Technol. 34(2) (2024)- 2021
- [j5]Kalaiselvi Thiruvenkadam, Kalaichelvi Nagarajan, Padmanaban Sriramakrishnan:
An automatic self-initialized clustering method for brain tissue segmentation and pathology detection from magnetic resonance human head scans with graphics processing unit machine. Concurr. Comput. Pract. Exp. 33(6) (2021) - 2020
- [j4]Kalaiselvi Thiruvenkadam, Thiyagarajan Padmapriya, Padmanaban Sriramakrishnan, Venugopal Priyadharshini:
Development of automatic glioma brain tumor detection system using deep convolutional neural networks. Int. J. Imaging Syst. Technol. 30(4): 926-938 (2020) - [j3]T. Kalaiselvi, P. Kumarashankar, Padmanaban Sriramakrishnan:
Three-Phase Automatic Brain Tumor Diagnosis System Using Patches Based Updated Run Length Region Growing Technique. J. Digit. Imaging 33(2): 465-479 (2020)
2010 – 2019
- 2019
- [j2]Padmanaban Sriramakrishnan, Kalaiselvi Thiruvenkadam, Karuppana Gounder Somasundaram, Rajeswaran Rangasami:
A rapid knowledge-based partial supervision fuzzy c-means for brain tissue segmentation with CUDA-enabled GPU machine. Int. J. Imaging Syst. Technol. 29(4): 547-560 (2019) - 2018
- [j1]T. Kalaiselvi, Padmanaban Sriramakrishnan:
Rapid brain tissue segmentation process by modified FCM algorithm with CUDA enabled GPU machine. Int. J. Imaging Syst. Technol. 28(3): 163-174 (2018)
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