| Evaluation of 3D correspondence methods for model building MA Styner, KT Rajamani, LP Nolte, G Zsemlye, G Székely, CJ Taylor, ... Information Processing in Medical Imaging: 18th International Conference …, 2003 | 394 | 2003 |
| Statistical deformable bone models for robust 3D surface extrapolation from sparse data KT Rajamani, MA Styner, H Talib, G Zheng, LP Nolte, MAG Ballester Medical image analysis 11 (2), 99-109, 2007 | 171 | 2007 |
| Accurate and robust reconstruction of a surface model of the proximal femur from sparse-point data and a dense-point distribution model for surgical navigation G Zheng, X Dong, KT Rajamani, X Zhang, M Styner, RU Thoranaghatte, ... IEEE transactions on biomedical engineering 54 (12), 2109-2122, 2007 | 56 | 2007 |
| A novel attention-based gated recurrent unit and its efficacy in speech emotion recognition ST Rajamani, KT Rajamani, A Mallol-Ragolta, S Liu, B Schuller ICASSP 2021-2021 IEEE international conference on acoustics, speech and …, 2021 | 52 | 2021 |
| Brain tumor extraction from MRI brain images using marker based watershed algorithm CC Benson, VL Lajish, K Rajamani 2015 International Conference on advances in computing, communications and …, 2015 | 50 | 2015 |
| Bone model morphing for enhanced surgical visualization KT Rajamani, SC Joshi, MA Styner 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro …, 2004 | 48 | 2004 |
| Brain tumor segmentation from MR brain images using improved fuzzy c-means clustering and watershed algorithm CC Benson, V Deepa, VL Lajish, K Rajamani 2016 International Conference on advances in computing, communications and …, 2016 | 47 | 2016 |
| Gaussian process density counting from weak supervision M von Borstel, M Kandemir, P Schmidt, MK Rao, K Rajamani, ... Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 44 | 2016 |
| Automatic generation of 3D statistical shape models with optimal landmark distributions T Heimann, I Wolf, HP Meinzer Methods of Information in Medicine 46 (03), 275-281, 2007 | 35 | 2007 |
| Dynamic deformable attention network (DDANet) for COVID-19 lesions semantic segmentation KT Rajamani, H Siebert, MP Heinrich Journal of Biomedical Informatics 119, 103816, 2021 | 34 | 2021 |
| Exploring image classification of thyroid ultrasound images using deep learning KV Sai Sundar, KT Rajamani, S Siva Sankara Sai Proceedings of the International Conference on ISMAC in Computational Vision …, 2019 | 33 | 2019 |
| Bone morphing with statistical shape models for enhanced visualization KT Rajamani, J Hug, LP Nolte, M Styner Medical Imaging 2004: Visualization, Image-Guided Procedures, and Display …, 2004 | 33 | 2004 |
| Attention-augmented U-Net (AA-U-Net) for semantic segmentation KT Rajamani, P Rani, H Siebert, R ElagiriRamalingam, MP Heinrich Signal, image and video processing 17 (4), 981-989, 2023 | 30 | 2023 |
| A novel and stable approach to anatomical structure morphing for enhanced intraoperative 3D visualization KT Rajamani, MAG Ballester, LP Nolte, M Styner Medical Imaging 2005: Visualization, Image-Guided Procedures, and Display …, 2005 | 27 | 2005 |
| Use of a dense surface point distribution model in a three-stage anatomical shape reconstruction from sparse information for computer assisted orthopaedic surgery: A … G Zheng, KT Rajamani, LP Nolte Asian Conference on Computer Vision, 52-60, 2006 | 24 | 2006 |
| A comparison study assessing the feasibility of ultrasound-initialized deformable bone models H Talib, K Rajamani, J Kowal, LP Nolte, M Styner, MAG Ballester Computer Aided Surgery 10 (5-6), 293-299, 2005 | 22 | 2005 |
| Machine learning algorithm for retinal image analysis R Santhakumar, M Tandur, ER Rajkumar, KS Geetha, G Haritz, ... 2016 IEEE Region 10 Conference (TENCON), 1236-1240, 2016 | 21 | 2016 |
| Multiple instance learning: Robust validation on retinopathy of prematurity P Rani, R Elagiri Ramalingam, KT Rajamani, M Kandemir, D Singh Int J Ctrl Theory Appl 9, 451-459, 2016 | 21 | 2016 |
| Real-time vision based driver drowsiness detection using partial least squares analysis K Selvakumar, J Jerome, K Rajamani, N Shankar Journal of Signal Processing Systems 85, 263-274, 2016 | 20 | 2016 |
| Variational Weakly Supervised Gaussian Processes. M Kandemir, M Haussmann, F Diego, KT Rajamani, J Van Der Laak, ... BMVC, 71.1-71.12, 2016 | 16 | 2016 |
Martin StynerProfessor of Computer Science and Psychiatry, University of North Carolina at Chapel HillVerified email at unc.edu