ESD-VesNet: uncertainty-aware vessel segmentation network for endoscopic submucosal dissection with hard negative mining - Scorecard - MDSpire

ESD-VesNet: uncertainty-aware vessel segmentation network for endoscopic submucosal dissection with hard negative mining

  • By

  • Mengya Xu

  • Ming Chen

  • Zhen Li

  • Chaoyang Lyu

  • An Wang

  • Rulin Zhou

  • Chuanhao Zhao

  • Jiaxun Xiang

  • Tsz Chun Wong

  • Hossein Farahnaki

  • Sobhan Zamani Kiasari

  • Tong Wu

  • Zimeng Su

  • Yile Zeng

  • Ruijing Wen

  • Xiaohan Shang

  • Yi Mu

  • Kezhen Lin

  • Yidong Zhang

  • Hongliang Ren

  • July 3, 2026

  • 0 min

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Clinical Scorecard: Uncertainty-Driven Vessel Segmentation Network for Endoscopic Submucosal Dissection Incorporating Hard Negative Mining Techniques

At a Glance

CategoryDetail
ConditionEndoscopic Submucosal Dissection (ESD)
Key MechanismsAI-assisted real-time detection and segmentation of vessels to minimize intraoperative bleeding risk.
Target PopulationPatients undergoing ESD for early-stage gastrointestinal cancers.
Care SettingMinimally invasive surgical environments.

Key Highlights

  • Proposes ESD-VesNet for accurate vessel detection and segmentation in ESD procedures.
  • Introduces the ESD-Vessel dataset with 2401 annotated vessel frames and 708 hard negative frames.
  • Integrates evidential deep learning for uncertainty quantification and hard negative mining.

Guideline-Based Recommendations

Diagnosis

  • Utilize AI-assisted tools for improved vessel detection rates during ESD.

Management

  • Perform pre-coagulation on potential vessels to prevent intraoperative bleeding.

Monitoring & Follow-up

  • Monitor for intraoperative bleeding and manage it promptly to maintain surgical field clarity.

Risks

  • Intraoperative bleeding can obscure the surgical field and prolong procedures.

Patient & Prescribing Data

Patients with early-stage gastrointestinal cancers undergoing ESD.

AI tools can enhance vessel detection and reduce complications during ESD.

Clinical Best Practices

  • Incorporate AI-assisted vessel segmentation to improve procedural safety.
  • Utilize high-quality annotated datasets for training segmentation models.

Related Resources & Content

Original Source(s)

ESD-VesNet: uncertainty-aware vessel segmentation network for endoscopic submucosal dissection with hard negative mining

  • by Mengya Xu, Ming Chen, Zhen Li, Chaoyang Lyu, An Wang, Rulin Zhou, Chuanhao Zhao, Jiaxun Xiang, Tsz Chun Wong, Hossein Farahnaki, Sobhan Zamani Kiasari, Tong Wu, Zimeng Su, Yile Zeng, Ruijing Wen, Xiaohan Shang, Yi Mu, Kezhen Lin, Yidong Zhang, Hongliang Ren

  • July 3, 2026

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