| Automated assessment of COVID-19 reporting and data system and chest CT severity scores in patients suspected of having COVID-19 using artificial intelligence N Lessmann, CI Sánchez, L Beenen, LH Boulogne, M Brink, E Calli, ... Radiology 298 (1), E18-E28, 2021 | 166* | 2021 |
| 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 | 88 | 2017 |
| Deep learning for malignancy risk estimation of pulmonary nodules detected at low-dose screening CT KV Venkadesh, AAA Setio, A Schreuder, ET Scholten, K Chung, ... Radiology 300 (2), 438-447, 2021 | 82 | 2021 |
| 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 | 65 | 2016 |
| Unboxing AI-radiological insights into a deep neural network for lung nodule characterization VK Venugopal, K Vaidhya, M Murugavel, A Chunduru, V Mahajan, ... Academic radiology 27 (1), 88-95, 2020 | 32 | 2020 |
| LNDb challenge on automatic lung cancer patient management J Pedrosa, G Aresta, C Ferreira, G Atwal, HA Phoulady, X Chen, R Chen, ... Medical image analysis 70, 102027, 2021 | 18 | 2021 |
| Lung nodule malignancy prediction in sequential ct scans: Summary of isbi 2018 challenge Y Balagurunathan, A Beers, M Mcnitt-Gray, L Hadjiiski, S Napel, ... IEEE transactions on medical imaging 40 (12), 3748-3761, 2021 | 16 | 2021 |
| Improving automated covid-19 grading with convolutional neural networks in computed tomography scans: An ablation study C de Vente, LH Boulogne, KV Venkadesh, C Sital, N Lessmann, C Jacobs, ... arXiv preprint arXiv:2009.09725, 2020 | 14 | 2020 |
| An automated workflow for lung nodule follow-up recommendation using deep learning KC Kaluva, K Vaidhya, A Chunduru, S Tarai, SPP Nadimpalli, S Vaidya Image Analysis and Recognition: 17th International Conference, ICIAR 2020 …, 2020 | 10 | 2020 |
| Automated COVID-19 grading with convolutional neural networks in computed tomography scans: a systematic comparison C de Vente, LH Boulogne, KV Venkadesh, C Sital, N Lessmann, C Jacobs, ... IEEE transactions on artificial intelligence 3 (2), 129-138, 2021 | 8* | 2021 |
| Prediction variability to identify reduced AI performance in cancer diagnosis at MRI and CT N Alves, JS Bosma, KV Venkadesh, C Jacobs, Z Saghir, M de Rooij, ... Radiology 308 (3), e230275, 2023 | 7 | 2023 |
| Prior CT improves deep learning for malignancy risk estimation of screening-detected pulmonary nodules KV Venkadesh, TA Aleef, ET Scholten, Z Saghir, M Silva, N Sverzellati, ... Radiology 308 (2), e223308, 2023 | 4 | 2023 |
| Towards radiologist-level malignancy detection on chest CT scans: a comparative study of the performance of convolutional neural networks and four thoracic radiologists V Venugopal, A Vaidya, A Ahuja, Y Singh, K Vaidhya, A Raj, V Mahajan, ... European Congress of Radiology-ECR 2019, 2019 | 1 | 2019 |
| Enhancing a deep learning model for pulmonary nodule malignancy risk estimation in chest CT with uncertainty estimation D Peeters, N Alves, KV Venkadesh, R Dinnessen, Z Saghir, ET Scholten, ... European Radiology, 1-13, 2024 | | 2024 |
| Erratum for: Prediction Variability to Identify Reduced AI Performance in Cancer Diagnosis at MRI and CT N Alves, JS Bosma, KV Venkadesh, C Jacobs, Z Saghir, M de Rooij, ... Radiology 309 (1), e239023, 2023 | | 2023 |
| Lung Nodule Malignancy Prediction in Sequential CT Scans: Summary of ISBI 2018 Challenge. L Hadjiiski, S Napel, D Goldgof, G Perez, P Arbelaez, A Mehrtash, ... IEEE Transactions on Medical Imaging 40 (12), 2021 | | 2021 |
| Cloud-based semi-automated liver segmentation: analytical study to compare its speed and accuracy with a semi-automated workstation based software V Venugopal, A Chunduru, M Barnwal, DS Mahra, A Raj, K Vaidhya, ... European Congress of Radiology-ECR 2019, 2019 | | 2019 |
Colin JacobsRadboudumc, Nijmegen, The NetherlandsVerified email at radboudumc.nl
