license: apache-2.0
task_categories:
- image-text-to-text
3D-RAD
The official Dataset for the paper "3D-RAD: A Comprehensive 3D Radiology Med-VQA Dataset with Multi-Temporal Analysis and Diverse Diagnostic Tasks".
In our project, we collect a large-scale dataset designed to advance 3D Med-VQA using radiology CT scans, 3D-RAD, encompasses six diverse VQA tasks: anomaly detection (task 1), image observation (task 2), medical computation (task 3), existence detection (task 4), static temporal diagnosis (task 5), and longitudinal temporal diagnosis (task 6).
📁 Images/
This folder contains preprocessed 3D CT volumes in .npy format.
Each file is structured to facilitate direct input into vision-language models.
- Purpose: Standardized model input across all tasks.
📁 train/ and 📁 test/
These folders contain the question-answer (QA) pairs categorized by task.
Each file corresponds to a specific QA task such as anomaly detection, measurement, or temporal reasoning.
train/: QA pairs for model trainingtest/: QA pairs for model evaluation
Fields:
VolumeName: File name of the associated CT volume (matches the file inImages/)Question: The natural language questionAnswer: The ground truth answerQuestionType: EitheropenorclosedAnswerChoice: Correct option (A/B/C/D) for closed questionsChoice A–Choice D: Candidate options for closed questions
Code
You can find our code in M3D-RAD_Code.
M3D-RAD Model
You can find our model in M3D-RAD_Models.
Data Source
The original CT scans in our dataset are derived from CT-RATE, which is released under a CC-BY-NC-SA license. We fully comply with the license terms by using the data for non-commercial academic research, providing proper attribution.