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Kenli Li

4 papers hereh-index 9272 citations36 works total

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

author position
  • middle author2
  • last author2

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

fields
  • cs.CV3
  • cs.AI1
same name
  • Kenli Li — 12 papers, h 4
  • Kenli Li — 11 papers, h 66
  • Kenli Li — 7 papers, h 12
  • Kenli Li — 4 papers
  • KenLi Li — 4 papers, h 27
  • Kenli Li — 2 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

FUSEP: A Multi-Center Benchmark for Diverse Tasks in Early Pregnancy Fetal Ultrasound Screening

Bin Pu, Jiewen Yang, Liwen Wang +9

A large number of infants with congenital anomalies are born each year globally, especially in areas with underdeveloped medical resources. Currently, fetal ultrasound screening is…

cs.CV2026

Anatomy-Anchored Self-Supervision: Distilling Vision Foundation Models for Invariant Ultrasound Representation

Chunzheng Zhu, Yijun Wang, Jianxin Lin +5

Self-supervised pre-training paradigm has gained increasing prominence for learning transferable representations in medical imaging, yet existing methods for ultrasound (US) images…

cs.CV2026

Subspace-Guided Semantic and Topological Invariant Registration for Annotation-Free Ultrasound Plane Quality Control

Chunzheng Zhu, Jianxin Lin, Feng Wang +5

Reliable quality control (QC) of ultrasound images is essential for both real-time acquisition guidance and retrospective clinical audit, yet existing approaches rely heavily on pe…

cs.CV2025

Hulu-Med: A Transparent Generalist Model towards Holistic Medical Vision-Language Understanding

Songtao Jiang, Yuan Wang, Sibo Song +22

Real-world clinical decision-making requires integrating heterogeneous data, including medical text, 2D images, 3D volumes, and videos, while existing AI systems fail to unify all…

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