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researcher

E. Smistad

10 papers hereh-index 252.8k citations94 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author5
  • last author3

Across the 8 of 10 papers where every author was matched, so the position is known.

fields
  • eess.IV7
  • cs.CV1
  • cs.LG1
  • q-bio.QM1

identity via Semantic Scholar / OpenAlex

activity
20192025
most citedDeep Learning for Segmentation using an Open Large-Scale Dataset in 2D Echocardiography

773 citations · 785 across the 10 of their papers we have counts for

collaborators
Showing 2021Show all

2 papers · 1 filter

eess.IV2021★ 1 cited

Hybrid guiding: A multi-resolution refinement approach for semantic segmentation of gigapixel histopathological images

André Pedersen, Erik Smistad, Tor V. Rise +6

Histopathological cancer diagnostics has become more complex, and the increasing number of biopsies is a challenge for most pathology laboratories. Thus, development of automatic m…

q-bio.QM2021

Code-free development and deployment of deep segmentation models for digital pathology

Henrik Sahlin Pettersen, Ilya Belevich, Elin Synnøve Røyset +5

Application of deep learning on histopathological whole slide images (WSIs) holds promise of improving diagnostic efficiency and reproducibility but is largely dependent on the abi…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.