◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

H. Kalabizadeh

3 papers hereh-index 26 citations5 works total

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

fields
  • cs.CV2
  • eess.IV1

identity via Semantic Scholar / OpenAlex

most citedBeyond Benchmarks of IUGC: Rethinking Requirements of Deep Learning Methods for Intrapartum Ultrasound Biometry from Fetal Ultrasound Videos

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

collaborators

3 papers

cs.CV2026★ 1 cited

Beyond Benchmarks of IUGC: Rethinking Requirements of Deep Learning Methods for Intrapartum Ultrasound Biometry from Fetal Ultrasound Videos

Jieyun Bai, Zihao Zhou, Yitong Tang +60

A substantial proportion (45\%) of maternal deaths, neonatal deaths, and stillbirths occur during the intrapartum phase, with a particularly high burden in low- and middle-income c…

cs.CV2025

Unsupervised Domain Adaptation via Content Alignment for Hippocampus Segmentation

Hoda Kalabizadeh, Ludovica Griffanti, Pak-Hei Yeung +3

Deep learning models for medical image segmentation often struggle when deployed across different datasets due to domain shifts - variations in both image appearance, known as styl…

eess.IV2025

Automated Fetal Biometry Assessment with Deep Ensembles using Sparse-Sampling of 2D Intrapartum Ultrasound Images

Jayroop Ramesh, Valentin Bacher, Mark C. Eid +6

The International Society of Ultrasound advocates Intrapartum Ultrasound (US) Imaging in Obstetrics and Gynecology (ISUOG) to monitor labour progression through changes in fetal he…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.