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Sailesh Conjeti
Sailesh Conjeti
Siemens Healthineers
Verified email at siemens-healthineers.com - Homepage
Title
Cited by
Cited by
Year
ReLayNet: retinal layer and fluid segmentation of macular optical coherence tomography using fully convolutional networks
AG Roy, S Conjeti, SPK Karri, D Sheet, A Katouzian, C Wachinger, ...
Biomedical optics express 8 (8), 3627-3642, 2017
3742017
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support: 4th International Workshop, DLMIA 2018, and 8th International Workshop, ML-CDS …
D Stoyanov, Z Taylor, G Carneiro, T Syeda-Mahmood, A Martel, ...
Springer, 2018
2082018
QuickNAT: A fully convolutional network for quick and accurate segmentation of neuroanatomy
AG Roy, S Conjeti, N Navab, C Wachinger, ...
NeuroImage 186, 713-727, 2019
165*2019
A comparative evaluation of neural network classifiers for stress level analysis of automotive drivers using physiological signals
RR Singh, S Conjeti, R Banerjee
Biomedical Signal Processing and Control 8 (6), 740-754, 2013
1582013
Prediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open …
PCCD Community
The Lancet Oncology, 2016
127*2016
Fastsurfer-a fast and accurate deep learning based neuroimaging pipeline
L Henschel, S Conjeti, S Estrada, K Diers, B Fischl, M Reuter
NeuroImage 219, 117012, 2020
1072020
Error corrective boosting for learning fully convolutional networks with limited data
AG Roy, S Conjeti, D Sheet, A Katouzian, N Navab, C Wachinger
International Conference on Medical Image Computing and Computer-Assisted …, 2017
87*2017
Generalizability vs. Robustness: Investigating Medical Imaging Networks Using Adversarial Examples
M Paschali, S Conjeti, F Navarro, N Navab
International Conference on Medical Image Computing and Computer-Assisted …, 2018
80*2018
Bayesian QuickNAT: Model uncertainty in deep whole-brain segmentation for structure-wise quality control
AG Roy, S Conjeti, N Navab, C Wachinger, ...
NeuroImage 195, 11-22, 2019
642019
Inherent brain segmentation quality control from fully convnet monte carlo sampling
AG Roy, S Conjeti, N Navab, C Wachinger
International Conference on Medical Image Computing and Computer-Assisted …, 2018
642018
CATARACTS: Challenge on automatic tool annotation for cataRACT surgery
H Al Hajj, M Lamard, PH Conze, S Roychowdhury, X Hu, G Maršalkaitė, ...
Medical image analysis 52, 24-41, 2019
602019
Multiple instance learning of deep convolutional neural networks for breast histopathology whole slide classification
K Das, S Conjeti, AG Roy, J Chatterjee, D Sheet
2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018 …, 2018
482018
Survival analysis for high-dimensional, heterogeneous medical data: Exploring feature extraction as an alternative to feature selection
S Pölsterl, S Conjeti, N Navab, A Katouzian
Artificial intelligence in medicine 72, 1-11, 2016
432016
An approach for real-time stress-trend detection using physiological signals in wearable computing systems for automotive drivers
RR Singh, S Conjeti, R Banerjee
2011 14th International IEEE Conference on Intelligent Transportation …, 2011
432011
Human motion analysis with deep metric learning
H Coskun, DJ Tan, S Conjeti, N Navab, F Tombari
Proceedings of the European Conference on Computer Vision (ECCV), 667-683, 2018
382018
FatSegNet: A fully automated deep learning pipeline for adipose tissue segmentation on abdominal dixon MRI
S Estrada, R Lu, S Conjeti, X Orozco‐Ruiz, J Panos‐Willuhn, ...
Magnetic resonance in medicine 83 (4), 1471-1483, 2020
372020
Lumen Segmentation in Intravascular Optical Coherence Tomography using Backscattering Tracked and Initialized Random Walks
A Guha Roy, S Conjeti, S Carlier, P Dutta, A Kastrati, A Laine, N Navab, ...
IEEE Journal of Biomedical and Health Informatics, 2015
352015
Heterogeneous ensembles for predicting survival of metastatic, castrate-resistant prostate cancer patients
NN Sebastian Pölsterl, Pankaj Gupta, Lichao Wang, Sailesh Conjeti, Amin ...
F1000Research 5 (2676), 2016
33*2016
Deeply learnt hashing forests for content based image retrieval in prostate MR images
A Shah, S Conjeti, N Navab, A Katouzian
Medical Imaging 2016: Image Processing 9784, 978414, 2016
322016
Assessment of driver stress from physiological signals collected under real-time semi-urban driving scenarios
RR Singh, S Conjeti, R Banerjee
International Journal of Computational Intelligence Systems 7 (5), 909-923, 2014
302014
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