|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
|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
|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
|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
|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
|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
International Workshop on Statistical Atlases and Computational Models of …, 2017
|Generative adversarial networks for brain lesion detection|
V Alex, MS KP, SS Chennamsetty, G Krishnamurthi
Medical Imaging 2017: Image Processing 10133, 113-121, 2017
|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, 2017
|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
|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
|Brain tumor segmentation using dense fully convolutional neural network|
M Shaikh, G Anand, G Acharya, A Amrutkar, V Alex, G Krishnamurthi
International MICCAI brainlesion workshop, 309-319, 2017
|Multi-modal brain tumor segmentation using stacked denoising autoencoders|
K Vaidhya, S Thirunavukkarasu, V Alex, G Krishnamurthi
BrainLes 2015, 181-194, 2015
|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
|Medical image retrieval using Resnet-18|
S Ayyachamy, V Alex, M Khened, G Krishnamurthi
Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and …, 2019
|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
|Prostate tissue characterization/classification in 144 patient population using wavelet and higher order spectra features from transrectal ultrasound images|
G Pareek, UR Acharya, SV Sree, G Swapna, R Yantri, RJ Martis, L Saba, ...
Technology in cancer research & treatment 12 (6), 545-557, 2013
|Atheromatic™: Symptomatic vs. asymptomatic classification of carotid ultrasound plaque using a combination of HOS, DWT & texture|
UR Acharya, O Faust, SV Sree, APC Alvin, G Krishnamurthi, J Sanches, ...
2011 Annual International Conference of the IEEE Engineering in Medicine and …, 2011
|Demystifying brain tumor segmentation networks: interpretability and uncertainty analysis|
P Natekar, A Kori, G Krishnamurthi
Frontiers in computational neuroscience 14, 6, 2020
|Longitudinal multiple sclerosis lesion segmentation using 3D convolutional neural networks|
S Vaidya, A Chunduru, R Muthuganapathy, G Krishnamurthi
Proceedings of the 2015 longitudinal multiple sclerosis lesion segmentation …, 2015
|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), 1-14, 2021