| Imaging biomarkers in neurodegeneration: current and future practices PNE Young, M Estarellas, E Coomans, M Srikrishna, H Beaumont, ... Alzheimer's research & therapy 12, 1-17, 2020 | 173 | 2020 |
| Deep learning from MRI-derived labels enables automatic brain tissue classification on human brain CT M Srikrishna, JB Pereira, RA Heckemann, G Volpe, D van Westen, ... Neuroimage 244, 118606, 2021 | 16 | 2021 |
| Comparison of two-dimensional-and three-dimensional-based U-Net architectures for brain tissue classification in one-dimensional brain CT M Srikrishna, RA Heckemann, JB Pereira, G Volpe, A Zettergren, S Kern, ... Frontiers in Computational Neuroscience 15, 785244, 2022 | 15 | 2022 |
| Imaging biomarkers in neurodegeneration: current and future practices. Alzheimer’s Res. Ther. 12 (1), 49 PNE Young, M Estarellas, E Coomans, M Srikrishna, H Beaumont, ... | 5 | 2020 |
| Imaging biomarkers in neurodegeneration: current and future practices. Alzheimers Res Ther. 2020; 12: 49 PNE Young, M Estarellas, E Coomans, M Srikrishna, H Beaumont, ... PUBMED, 0 | 4 | |
| CT‐based volumetric measures obtained through deep learning: Association with biomarkers of neurodegeneration M Srikrishna, NJ Ashton, A Moscoso, JB Pereira, RA Heckemann, ... Alzheimer's & Dementia 20 (1), 629-640, 2024 | 2 | 2024 |
| CT‐based brain segmentation and volumetry using deep learning methods: Neuroimaging/Optimal neuroimaging measures for early detection M Srikrishna, JB Pereira, RA Heckemann, G Volpe, A Zettergren, S Kern, ... Alzheimer's & Dementia 16, e045824, 2020 | 1 | 2020 |
| Chemical signatures delineate heterogeneous amyloid plaque populations across the Alzheimer’s disease spectrum S Koutarapu, J Ge, M Dulewicz, M Srikrishna, A Szadziewska, J Wood, ... bioRxiv, 2024 | | 2024 |
| Assessing CT-based Volumetric Analysis via Transfer Learning with MRI and Manual Labels for Idiopathic Normal Pressure Hydrocephalus M Srikrishna, W Seo, A Zettergren, S Kern, D Cantré, F Gessler, ... medRxiv, 2024.06. 23.24309144, 2024 | | 2024 |
| Chemical imaging signatures delineate heterogeneous amyloid plaque populations across the Alzheimers disease spectrum S Koutarapu, M Dulewicz, M Srikrishna, A Szadziewska, J Wood, ... bioRxiv, 2024.06. 03.596890, 2024 | | 2024 |
| User experience and biomarker associations of remotely administered and unsupervised smartphone‐based cognitive testing in a community sample of older adults F Öhman, I Bosch, D Berron, M Srikrishna, F Heeman, J Skoog, ... Alzheimer's & Dementia 19, e083050, 2023 | | 2023 |
| Assessing the clinical application of deep-learning-derived CT volumetric measures in neurodegenerative disease diagnostics M Srikrishna, NJ Ashton, A Moscoso, JB Pereira, RA Heckemann, ... medRxiv, 2022.12. 19.22282455, 2022 | | 2022 |
| Deriving biomarkers from computed tomography using deep learning M Srikrishna | | 2022 |
| Automated quantification of lateral ventricle volumes in normal pressure hydrocephalus from computed tomography scans using deep learning M Srikrishna, W Seo, J Virhammar, D Fallmar, M Scholl FLUIDS AND BARRIERS OF THE CNS 19, 2022 | | 2022 |
| Association of deep‐learning–derived brain computed tomography measures with cognition and blood‐based biomarkers of neurodegenerative diseases M Srikrishna, NJ Ashton, JB Pereira, RA Heckemann, D Westen, G Volpe, ... Alzheimer's & Dementia 17, e055910, 2021 | | 2021 |
| Deep learning-based human CT brain segmentation using MR derived labels M Srikrishna, JP Periera, RA Heckemann, G Volpe, A Zettergren, S Kern, ... Emerging Topics in Artificial Intelligence 2020 11469, 114690V, 2020 | | 2020 |
