mlsanityData to 7 Oct 2026

CT-AGRG: Automated Abnormality-Guided Report Generation from 3D Chest CT Volumes

arXiv 2408.11965 ↗First posted 21 Aug 2024eess.IV cs.CVcited by 10

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Abstract (arXiv)

The rapid increase of computed tomography (CT) scans and their time-consuming manual analysis have created an urgent need for robust automated analysis techniques in clinical settings. These aim to assist radiologists and help them managing their growing workload. Existing methods typically generate entire reports directly from 3D CT images, without explicitly focusing on observed abnormalities. This unguided approach often results in repetitive content or incomplete reports, failing to prioritize anomaly-specific descriptions. We propose a new anomaly-guided report generation model, which first predicts abnormalities and then generates targeted descriptions for each. Evaluation on a public dataset demonstrates significant improvements in report quality and clinical relevance. We extend our work by conducting an ablation study to demonstrate its effectiveness.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 42 of its 87 references that are in the map. First posted on arXiv 21 Aug 2024.

Builds on

42 of 87 references.

References · 42

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30 more
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 3; 2026: 7.

10 papers.

  1. 2025CT-Agent: A Multimodal-LLM Agent for 3D CT Radiology Question Answeringcited by 20
  2. 2026OmniCT: Towards a Unified Slice-Volume LVLM for Comprehensive CT Analysiscited by 9
  3. 2025CT-GRAPH: Hierarchical Graph Attention Network for Anatomy-Guided CT Report Generationcited by 8
  4. 2026Enhancing Fine-Grained Spatial Grounding in 3D CT Report Generation via Discriminative Guidancecited by 3
  5. 2026Generating Reports or Repeating Templates? Measuring and Mitigating Template Collapse in 3D CT Report Generationcited by 3
  6. 2025Recurrent Visual Feature Extraction and Stereo Attentions for CT Report Generationcited by 2
  7. 2026CTest-Metric: A Unified Framework to Assess Clinical Validity of Metrics for CT Report Generationcited by 2
  8. 2026Revisiting LLM Adaptation for 3D CT Report Generation: A Study of Scaling and Diagnostic Priorscited by 1
  9. 2026NV-Reason-CT: 3D Visual Language Model for CT Analysiscited by 0
  10. 2026SelfCue: Making a 3D CT Report Generator Say What It Already Knowscited by 0