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Ganapathy Krishnamurthi
Ganapathy Krishnamurthi
Associate Professor at IIT-Madras
Bestätigte E-Mail-Adresse bei iitm.ac.in
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Zitiert von
Jahr
Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ...
arXiv preprint arXiv:1811.02629, 2018
17852018
Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: is the problem solved?
O Bernard, A Lalande, C Zotti, F Cervenansky, X Yang, PA Heng, I Cetin, ...
IEEE transactions on medical imaging 37 (11), 2514-2525, 2018
14452018
The liver tumor segmentation benchmark (lits)
P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ...
Medical Image Analysis 84, 102680, 2023
9432023
Fully convolutional multi-scale residual DenseNets for cardiac segmentation and automated cardiac diagnosis using ensemble of classifiers
M Khened, VA Kollerathu, G Krishnamurthi
Medical image analysis 51, 21-45, 2019
3452019
Longitudinal multiple sclerosis lesion segmentation: resource and challenge
A Carass, S Roy, A Jog, JL Cuzzocreo, E Magrath, A Gherman, J Button, ...
NeuroImage 148, 77-102, 2017
3172017
Data mining framework for fatty liver disease classification in ultrasound: a hybrid feature extraction paradigm
UR Acharya, SV Sree, R Ribeiro, G Krishnamurthi, RT Marinho, ...
Medical physics 39 (7Part1), 4255-4264, 2012
1302012
A generalized deep learning framework for whole-slide image segmentation and analysis
M Khened, A Kori, H Rajkumar, G Krishnamurthi, B Srinivasan
Scientific reports 11 (1), 11579, 2021
1292021
Densely connected fully convolutional network for short-axis cardiac cine MR image segmentation and heart diagnosis using random forest
M Khened, V Alex, G Krishnamurthi
Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS …, 2018
1132018
Generative adversarial networks for brain lesion detection
V Alex, MS KP, SS Chennamsetty, G Krishnamurthi
Medical Imaging 2017: Image Processing 10133, 113-121, 2017
972017
Semisupervised learning using denoising autoencoders for brain lesion detection and segmentation
V Alex, K Vaidhya, S Thirunavukkarasu, C Kesavadas, G Krishnamurthi
Journal of Medical Imaging 4 (4), 041311-041311, 2017
882017
PAIP 2019: Liver cancer segmentation challenge
YJ Kim, H Jang, K Lee, S Park, SG Min, C Hong, JH Park, K Lee, J Kim, ...
Medical image analysis 67, 101854, 2021
872021
Medical image retrieval using Resnet-18
S Ayyachamy, V Alex, M Khened, G Krishnamurthi
Medical imaging 2019: imaging informatics for healthcare, research, and …, 2019
832019
Understanding symptomatology of atherosclerotic plaque by image-based tissue characterization
UR Acharya, O Faust, APC Alvin, G Krishnamurthi, JCR Seabra, ...
Computer methods and programs in biomedicine 110 (1), 66-75, 2013
832013
Demystifying brain tumor segmentation networks: interpretability and uncertainty analysis
P Natekar, A Kori, G Krishnamurthi
Frontiers in computational neuroscience 14, 6, 2020
802020
Brain tumor segmentation using dense fully convolutional neural network
M Shaikh, G Anand, G Acharya, A Amrutkar, V Alex, G Krishnamurthi
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2018
762018
Segmentation and classification in digital pathology for glioma research: challenges and deep learning approaches
T Kurc, S Bakas, X Ren, A Bagari, A Momeni, Y Huang, L Zhang, A Kumar, ...
Frontiers in neuroscience 14, 27, 2020
722020
2018 robotic scene segmentation challenge
M Allan, S Kondo, S Bodenstedt, S Leger, R Kadkhodamohammadi, ...
arXiv preprint arXiv:2001.11190, 2020
702020
2D-densely connected convolution neural networks for automatic liver and tumor segmentation
KC Kaluva, M Khened, A Kori, G Krishnamurthi
arXiv preprint arXiv:1802.02182, 2018
702018
Multi-modal brain tumor segmentation using stacked denoising autoencoders
K Vaidhya, S Thirunavukkarasu, V Alex, G Krishnamurthi
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2016
662016
Hypothesis validation of far-wall brightness in carotid-artery ultrasound for feature-based IMT measurement using a combination of level-set segmentation and registration
F Molinari, G Krishnamurthi, UR Acharya, SV Sree, G Zeng, L Saba, ...
IEEE Transactions on Instrumentation and measurement 61 (4), 1054-1063, 2012
602012
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