mlsanityData to 14 Oct 2026

A Chain-of-thought Reasoning Breast Ultrasound Dataset Covering All Histopathology Categories

arXiv 2509.17046 ↗First posted 21 Sep 2025eess.IV cs.AI cs.CVcited by 6

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Abstract (arXiv)

Breast ultrasound (BUS) is an essential tool for diagnosing breast lesions, with millions of examinations per year. However, publicly available high-quality BUS benchmarks for AI development are limited in data scale and annotation richness. In this work, we present BUS-CoT, a BUS dataset for chain-of-thought (CoT) reasoning analysis, which contains 11,439 images of 10,019 lesions from 4,838 patients and covers all 99 histopathology types. To facilitate research on incentivizing CoT reasoning, we construct the reasoning processes based on observation, feature, diagnosis and pathology labels, annotated and verified by experienced experts. Moreover, by covering lesions of all histopathology types, we aim to facilitate robust AI systems in rare cases, which can be error-prone in clinical practice.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 10 of its 197 references that are in the map. First posted on arXiv 21 Sep 2025.

Builds on

10 of 197 references.

References · 10

  1. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  2. 2024GPT-4o System Cardcited by 4,588
  3. 2024Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolutioncited by 4,234
  4. 2021Deep Long-Tailed Learning: A Surveycited by 417
  5. 2019What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Usecited by 135
  6. 2022A Survey on Long-Tailed Visual Recognitioncited by 75
  7. 2017CycleGAN, a Master of Steganographycited by 65
  8. 2024Out-of-distribution Detection in Medical Image Analysis: A surveycited by 22
  9. 2024Knowledge-driven AI-generated data for accurate and interpretable breast ultrasound diagnosescited by 2
  10. 2025A Foundational Generative Model for Breast Ultrasound Image Analysiscited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 5.

6 papers.

  1. 2025UMind-VL: A Generalist Ultrasound Vision-Language Model for Unified Grounded Perception and Comprehensive Interpretationcited by 2
  2. 2026BreastGPT: A Multimodal Large Language Model for the Full Spectrum of Breast Cancer Clinical Routinecited by 1
  3. 2026Experience-Guided Self-Adaptive Cascaded Agents for Breast Cancer Screening and Diagnosis with Reduced Biopsy Referralscited by 0
  4. 2026UltrasoundAgents: Hierarchical Multi-Agent Evidence-Chain Reasoning for Breast Ultrasound Diagnosiscited by 0
  5. 2026Ultrasound Vision-Language Alignment via Contrastive Learningcited by 0
  6. 2026Look-Closer-Then-Diagnose: Confidence-Aware Ultrasound VQA via Active Zoomingcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026MammoExpert: Benchmarking Chain-of-Thought Reasoning in Mammography Diagnosis
  2. 2026TumorChain: Interleaved Multimodal Chain-of-Thought Reasoning for Traceable Clinical Tumor Analysis
  3. 2026M3CoTBench: Benchmark Chain-of-Thought of MLLMs in Medical Image Understanding
  4. 2026Boot-and-Feedback Framework for Generalist-Expert Model Collaboration in Breast Ultrasound Diagnosis
  5. 2026Latent-CURE for Breast Cancer Diagnosis
  6. 2025U2-BENCH: Benchmarking Large Vision-Language Models on Ultrasound Understanding
  7. 2026EviPathBench: Benchmarking Evidence Acquisition and Reasoning in Vision-Language Models for Whole-Slide Pathology
  8. 2026Less Annotation, More Interpretation: Prior-Guided Concept Bottleneck Models for Interpretable Cancer Imaging Diagnosis