scispace - formally typeset
S

Srinivas C. Turaga

Researcher at Howard Hughes Medical Institute

Publications -  52
Citations -  6295

Srinivas C. Turaga is an academic researcher from Howard Hughes Medical Institute. The author has contributed to research in topics: Segmentation & Deep learning. The author has an hindex of 21, co-authored 49 publications receiving 4822 citations. Previous affiliations of Srinivas C. Turaga include Center of Advanced European Studies and Research & Massachusetts Institute of Technology.

Papers
More filters
Journal ArticleDOI

Opportunities and obstacles for deep learning in biology and medicine.

TL;DR: It is found that deep learning has yet to revolutionize biomedicine or definitively resolve any of the most pressing challenges in the field, but promising advances have been made on the prior state of the art.
Journal ArticleDOI

Connectomic reconstruction of the inner plexiform layer in the mouse retina

TL;DR: Circuit motifs that emerge from the data indicate a functional mechanism for a known cellular response in a ganglion cell that detects localized motion, and predict that another ganglions cell is motion sensitive.
Journal ArticleDOI

Space–time wiring specificity supports direction selectivity in the retina

TL;DR: A mathematical model shows how such ‘space–time wiring specificity’ could endow SAC dendrites with receptive fields that are oriented in space–time and therefore respond selectively to stimuli that move in the outward direction from the soma.
Journal ArticleDOI

Convolutional networks can learn to generate affinity graphs for image segmentation

TL;DR: This work presents a machine learning approach to computing an affinity graph using a convolutional network (CN) trained using ground truth provided by human experts and shows that the CN affinity graph can be paired with any standard partitioning algorithm and improves segmentation accuracy significantly compared to standard hand-designed affinity functions.
Journal ArticleDOI

In Toto Imaging and Reconstruction of Post-Implantation Mouse Development at the Single-Cell Level

TL;DR: A light-sheet microscope is developed that adapts itself to the dramatic changes in size, shape, and optical properties of the post-implantation mouse embryo and captures its development from gastrulation to early organogenesis at the cellular level.