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Neel Dey: Invariances and Covariances of Medical Imaging

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Manage episode 388956549 series 2997170
Content provided by Anirban Mukhopadhyay, Henry Krumb, Anirban Mukhopadhyay, and Henry Krumb. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Anirban Mukhopadhyay, Henry Krumb, Anirban Mukhopadhyay, and Henry Krumb or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Neel Dey is a postdoctoral researcher at MIT CSAIL in Polina Golland’s Medical Vision Group, where he is building dense representation learning and domain randomization methods for data and compute-efficient learning tasks. Neel got his Ph.D. from New York University under Guido Gerig where he worked on generative models and inverse problems in medical image analysis.

E(3) x SO(3) - Equivariant Networks for Spherical Deconvolution in Diffusion MRI

AnyStar: Domain randomized universal star-convex 3D instance segmentation

  continue reading

78 episodes

Artwork
iconShare
 
Manage episode 388956549 series 2997170
Content provided by Anirban Mukhopadhyay, Henry Krumb, Anirban Mukhopadhyay, and Henry Krumb. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Anirban Mukhopadhyay, Henry Krumb, Anirban Mukhopadhyay, and Henry Krumb or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Neel Dey is a postdoctoral researcher at MIT CSAIL in Polina Golland’s Medical Vision Group, where he is building dense representation learning and domain randomization methods for data and compute-efficient learning tasks. Neel got his Ph.D. from New York University under Guido Gerig where he worked on generative models and inverse problems in medical image analysis.

E(3) x SO(3) - Equivariant Networks for Spherical Deconvolution in Diffusion MRI

AnyStar: Domain randomized universal star-convex 3D instance segmentation

  continue reading

78 episodes

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