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Ruixiang Tang

4 papers hereh-index 11 citations4 works total

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

author position
  • first author1
  • middle author2
  • last author1

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

fields
  • cs.CV3
  • cs.AI1
same name
  • Ruixiang Tang — 15 papers, h 7
  • Ruixiang Tang — 14 papers, h 6
  • Ruixiang Tang — 6 papers, h 1
  • Ruixiang Tang — 6 papers, h 17
  • Ruixiang Tang — 5 papers, h 3
  • Ruixiang Tang — 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

4 papers

cs.CV2025

Unified Multimodal Coherent Field: Synchronous Semantic-Spatial-Vision Fusion for Brain Tumor Segmentation

Mingda Zhang, Yuyang Zheng, Ruixiang Tang +2

Brain tumor segmentation requires accurate identification of hierarchical regions including whole tumor (WT), tumor core (TC), and enhancing tumor (ET) from multi-sequence magnetic…

cs.CV2025

A Semantic Segmentation Algorithm for Pleural Effusion Based on DBIF-AUNet

Ruixiang Tang, Mingda Zhang, Jianglong Qin +3

Pleural effusion semantic segmentation can significantly enhance the accuracy and timeliness of clinical diagnosis and treatment by precisely identifying disease severity and lesio…

cs.CV2025

DCFFSNet: Deep Connectivity Feature Fusion Separation Network for Medical Image Segmentation

Mingda Zhang, Xun Ye, Ruixiang Tang +1

Medical image segmentation leverages topological connectivity theory to enhance edge precision and regional consistency. However, existing deep networks integrating connectivity of…

cs.AI2025

A Multi-granularity Concept Sparse Activation and Hierarchical Knowledge Graph Fusion Framework for Rare Disease Diagnosis

Mingda Zhang, Na Zhao, Jianglong Qin +2

Despite advances from medical large language models in healthcare, rare-disease diagnosis remains hampered by insufficient knowledge-representation depth, limited concept understan…

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