| 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 | 2166 | 2018 |
| Eff-unet: A novel architecture for semantic segmentation in unstructured environment B Baheti, S Innani, S Gajre, S Talbar Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 292 | 2020 |
| Detection of distracted driver using convolutional neural network B Baheti, S Gajre, S Talbar Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 188 | 2018 |
| Brain tumor segmentation using cascaded deep convolutional neural network S Hussain, SM Anwar, M Majid 2017 39th annual International Conference of the IEEE engineering in …, 2017 | 169 | 2017 |
| MoNuSAC2020: A multi-organ nuclei segmentation and classification challenge R Verma, N Kumar, A Patil, NC Kurian, S Rane, S Graham, QD Vu, ... IEEE Transactions on Medical Imaging 40 (12), 3413-3423, 2021 | 168 | 2021 |
| MS-UNet: A multi-scale UNet with feature recalibration approach for automatic liver and tumor segmentation in CT images DT Kushnure, SN Talbar Computerized Medical Imaging and Graphics 89, 101885, 2021 | 126 | 2021 |
| Semantic scene segmentation in unstructured environment with modified DeepLabV3+ B Baheti, S Innani, S Gajre, S Talbar Pattern Recognition Letters 138, 223-229, 2020 | 114 | 2020 |
| Overall survival prediction in glioblastoma with radiomic features using machine learning U Baid, SU Rane, S Talbar, S Gupta, MH Thakur, A Moiyadi, A Mahajan Frontiers in computational neuroscience 14, 61, 2020 | 114 | 2020 |
| A novel approach for fully automatic intra-tumor segmentation with 3D U-Net architecture for gliomas U Baid, S Talbar, S Rane, S Gupta, MH Thakur, A Moiyadi, N Sable, ... Frontiers in computational neuroscience 14, 10, 2020 | 98 | 2020 |
| Local gray level S-curve transformation–a generalized contrast enhancement technique for medical images A Gandhamal, S Talbar, S Gajre, AFM Hani, D Kumar Computers in biology and medicine 83, 120-133, 2017 | 89 | 2017 |
| Deep deconvolutional residual network based automatic lung nodule segmentation G Singadkar, A Mahajan, M Thakur, S Talbar Journal of digital imaging 33, 678-684, 2020 | 88 | 2020 |
| Towards computationally efficient and realtime distracted driver detection with mobilevgg network B Baheti, S Talbar, S Gajre IEEE Transactions on Intelligent Vehicles 5 (4), 565-574, 2020 | 87 | 2020 |
| Brain extraction on MRI scans in presence of diffuse glioma: Multi-institutional performance evaluation of deep learning methods and robust modality-agnostic training S Thakur, J Doshi, S Pati, S Rathore, C Sako, M Bilello, SM Ha, G Shukla, ... Neuroimage 220, 117081, 2020 | 81 | 2020 |
| LNCDS: A 2D-3D cascaded CNN approach for lung nodule classification, detection and segmentation P Dutande, U Baid, S Talbar Biomedical signal processing and control 67, 102527, 2021 | 79 | 2021 |
| Nonsubsampled rotated complex wavelet transform (NSRCxWT) for medical image fusion related to clinical aspects in neurocysticercosis SS Chavan, A Mahajan, SN Talbar, S Desai, M Thakur, A D'cruz Computers in biology and medicine 81, 64-78, 2017 | 78 | 2017 |
| Deep learning radiomics algorithm for gliomas (drag) model: a novel approach using 3d unet based deep convolutional neural network for predicting survival in gliomas U Baid, S Talbar, S Rane, S Gupta, MH Thakur, A Moiyadi, S Thakur, ... Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2019 | 72 | 2019 |
| Motion estimation techniques for digital video coding S Metkar, S Talbar Springer, 2013 | 72 | 2013 |
| Independent component analysis of edge information for face recognition KJ Karande, SN Talbar Springer India, 2014 | 71 | 2014 |
| Prostate lesion segmentation in MR images using radiomics based deeply supervised U-Net P Hambarde, S Talbar, A Mahajan, S Chavan, M Thakur, N Sable Biocybernetics and Biomedical Engineering 40 (4), 1421-1435, 2020 | 59 | 2020 |
| Genetic fuzzy system (GFS) based wavelet co-occurrence feature selection in mammogram classification for breast cancer diagnosis MM Pawar, SN Talbar Perspectives in Science 8, 247-250, 2016 | 58 | 2016 |
Ujjwal Baid, Ph.D.Director of Research Operations, Emory University ([email protected])確認したメール アドレス: emory.edu