Das, Tilak

The multimodal brain tumor image segmentation benchmark (BRATS)

Menze, B. H., Jakab, A., Bauer, S., Kalpathy-Cramer, J., Farahani, K., Kirby, J., Burren, Y., Porz, N., Slotboom, J., Wiest, R., et al. (2015) · IEEE Transactions on Medical Imaging

Brain Tumor Detection and ClassificationMedical Image Segmentation Techniques

Cited by 6,781

Genetic disorders of vision revealed by a behavioral screen of 400 essential loci in zebrafish

Neuhauss, S. C. F., Biehlmaier, O., Seeliger, M. W., Das, T., Kohler, K., Harris, W. A., & Baier, H. (1999) · The Journal of Neuroscience

Retinal Development and DisordersZebrafish Biomedical Research Applications

Cited by 414

Decision Forests for Tissue-Specific Segmentation of High-Grade Gliomas in Multi-channel MR

Zikic, D., Glocker, B., Konukoglu, E., Criminisi, A., Demiralp, C., Shotton, J., Thomas, O. M., Das, T., Jena, R., & Price, S. J. (2012) · Lecture Notes in Computer Science

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 276

Multiclass semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning: an algorithm development and multicentre validation study

Monteiro, M., Newcombe, V. F. J., Mathieu, F., Adatia, K., Kamnitsas, K., Ferrante, E., Das, T., Whitehouse, D., Rueckert, D., Menon, D. K., et al. (2020) · The Lancet Digital Health

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 162

Brain injury in COVID-19 is associated with dysregulated innate and adaptive immune responses

Needham, E. J., Ren, A. L., Digby, R. J., Norton, E. J., Ebrahimi, S., Outtrim, J. G., Chatfield, D. A., Manktelow, A. E., Leibowitz, M. M., Newcombe, V. F. J., et al. (2022) · Brain

Long-Term Effects of COVID-19COVID-19 Clinical Research Studies

Cited by 90