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Kelly Payette

4 papers here

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

author position
  • first author1
  • middle author2

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • eess.IV2
  • cs.CV1
  • physics.med-ph1
ORCID 0000-0001-7041-0150

identity via Semantic Scholar / OpenAlex

activity
20232025
most citedWhy is the winner the best?

1 citations · 4 across the 4 of their papers we have counts for

collaborators

4 papers

eess.IV2025★ 1 cited

Pathological MRI Segmentation by Synthetic Pathological Data Generation in Fetuses and Neonates

Misha P. T Kaandorp, Damola Agbelese, Hosna Asma-ull +6

Developing new methods for the automated analysis of clinical fetal and neonatal MRI data is limited by the scarcity of annotated pathological datasets and privacy concerns that of…

physics.med-ph2024★ 1 cited

AutOmatic floW planning for fetaL MRI (OWL)

Sara Neves Silva, Tomas Woodgate, Sarah McElroy +11

Two subsequent deep learning networks, one localizing the fetal chest and one identifying a set of landmarks on a coronal whole-uterus balanced steady-state free precession scan, w…

eess.IV2023★ 1 cited

An automated pipeline for quantitative T2* fetal body MRI and segmentation at low field

Kelly Payette, Alena Uus, Jordina Aviles Verdera +9

Fetal Magnetic Resonance Imaging at low field strengths is emerging as an exciting direction in perinatal health. Clinical low field (0.55T) scanners are beneficial for fetal imagi…

cs.CV2023★ 1 cited

Why is the winner the best?

Matthias Eisenmann, Annika Reinke, Vivienn Weru +122

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to in…

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