Turaga, Srinivas C.

Opportunities and obstacles for deep learning in biology and medicine

Ching, T., Himmelstein, D. S., Beaulieu-Jones, B. K., Kalinin, A. A., Do, B. T., Way, G. P., Ferrero, E., Agapow, P.-M., Zietz, M., Hoffman, M. M., et al. (2018) · Journal of The Royal Society Interface

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 2,310

Connectomic reconstruction of the inner plexiform layer in the mouse retina

Helmstaedter, M., Briggman, K. L., Turaga, S. C., Jain, V., Seung, H. S., & Denk, W. (2013) · Nature

Visual perception and processing mechanismsNeuroscience and Neuropharmacology Research

Cited by 997

In toto imaging and reconstruction of post-implantation mouse development at the single-cell level

McDole, K., Guignard, L., Amat, F., Berger, A., Malandain, G., Royer, L. A., Turaga, S. C., Branson, K., & Keller, P. J. (2018) · Cell

Cell Image Analysis TechniquesAdvanced Fluorescence Microscopy Techniques

Cited by 522

Space–time wiring specificity supports direction selectivity in the retina

EyeWirers, T., Kim, J. S., Greene, M. J., Zlateski, A., Lee, K., Richardson, M., Turaga, S. C., Purcaro, M., Balkam, M., Robinson, A., et al. (2014) · Nature

Visual perception and processing mechanismsNeuroscience and Neuropharmacology Research

Cited by 450

Convolutional Networks Can Learn to Generate Affinity Graphs for Image Segmentation

Turaga, S. C., Murray, J. F., Jain, V., Roth, F., Helmstaedter, M., Briggman, K., Denk, W., & Seung, H. S. (2010) · Neural Computation

Medical Image Segmentation TechniquesAdvanced Neural Network Applications

Cited by 376

Supervised Learning of Image Restoration with Convolutional Networks

Jain, V., Murray, J. F., Roth, F., Turaga, S., Zhigulin, V., Briggman, K. L., Helmstaedter, M. N., Denk, W., & Seung, H. S. (2007) · 2007 IEEE 11th International Conference on Computer Vision

Image and Signal Denoising MethodsAdvanced Image Processing Techniques

Cited by 217

Automatic detection of synaptic partners in a whole-brain Drosophila electron microscopy data set

Buhmann, J., Sheridan, A., Malin-Mayor, C., Schlegel, P., Gerhard, S., Kazimiers, T., Krause, R., Nguyen, T. M., Heinrich, L., Lee, W.-C. A., et al. (2021) · Nature Methods

Cell Image Analysis TechniquesNeurobiology and Insect Physiology Research

Cited by 175

Connectome-constrained networks predict neural activity across the fly visual system

Lappalainen, J. K., Tschopp, F. D., Prakhya, S., McGill, M., Nern, A., Shinomiya, K., Takemura, S.-Y., Gruntman, E., Macke, J. H., & Turaga, S. C. (2024) · Nature

Neural dynamics and brain functionNeurobiology and Insect Physiology Research

Cited by 128

Connectome-constrained deep mechanistic networks predict neural responses across the fly visual system at single-neuron resolution

Lappalainen, J. K., Tschopp, F. D., Prakhya, S., McGill, M., Nern, A., Shinomiya, K., Takemura, S.-Y., Gruntman, E., Macke, J. H., & Turaga, S. C. (2023) · bioRxiv (Cold Spring Harbor Laboratory)

Neural dynamics and brain functionVisual perception and processing mechanisms

Cited by 31

A Connectome Based Hexagonal Lattice Convolutional Network Model of the Drosophila Visual System

Tschopp, F. D., Reiser, M. B., & Turaga, S. C. (2018) · arXiv

Visual perception and processing mechanismsNeurobiology and Insect Physiology Research

Cited by 24

Automatic Detection of Synaptic Partners in a Whole-Brain Drosophila EM Dataset

Buhmann, J., Sheridan, A., Gerhard, S., Krause, R., Nguyen, T., Heinrich, L., Schlegel, P., Lee, W.-C. A., Wilson, R., Saalfeld, S., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory)

Cell Image Analysis TechniquesNeurobiology and Insect Physiology Research

Cited by 21