X-iZhang commited on
Commit
159808a
ยท
verified ยท
1 Parent(s): 123935c

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +79 -0
README.md CHANGED
@@ -117,4 +117,83 @@ configs:
117
  data_files:
118
  - split: test
119
  path: impression_section/test-*
 
 
 
 
 
 
 
 
 
 
 
120
  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
117
  data_files:
118
  - split: test
119
  path: impression_section/test-*
120
+ task_categories:
121
+ - image-text-to-text
122
+ language:
123
+ - en
124
+ tags:
125
+ - chest-xray
126
+ - report-generation
127
+ - mimic-cxr
128
+ pretty_name: MIMIC-CXR Radiology Report Generation
129
+ size_categories:
130
+ - 1K<n<10K
131
  ---
132
+
133
+ # MIMIC-CXR-RRG: Radiology Report Generation Subsets
134
+
135
+ This dataset provides two carefully filtered and structured subsets from the [MIMIC-CXR](https://physionet.org/content/mimic-cxr/2.0.0/) dataset, specifically designed for **Radiology Report Generation (RRG)** tasks. It includes image-report pairs focused on the **Findings** and **Impression** sections, targeting **frontal-view chest X-rays** only.
136
+
137
+ ---
138
+
139
+ ## ๐Ÿ“š Dataset Overview
140
+
141
+ | Subset | Section Target | Split | #Samples | View Type |
142
+ |---------------------|--------------------|-------|----------|----------------|
143
+ | `findings_section` | Findings | test | 2361 | Frontal only |
144
+ | `impression_section`| Impression | test | 2343 | Frontal only |
145
+
146
+ - The splits **follow the evaluation protocol** used in models such as [Libra](https://x-izhang.github.io/Libra_v1.0/) and [MAIRA-2](https://arxiv.org/abs/2406.04449).
147
+ - Images and labels are provided in a test-only setting, useful for **benchmarking and zero-shot evaluation**.
148
+
149
+ ---
150
+
151
+ ## ๐Ÿงพ Data Format
152
+
153
+ Each instance in both subsets contains:
154
+
155
+ - ๐Ÿ“ท `main_image` โ€“ The frontal-view chest X-ray
156
+ - ๐Ÿ“ท `prior_image` โ€“ (Optional) Prior image if available
157
+ - ๐Ÿ“ Text sections:
158
+ - `findings_section`
159
+ - `impression_section`
160
+ - `indication_section`
161
+ - `comparison_section`
162
+ - `technique_section`
163
+ - `history_section`
164
+ - `examination_section`
165
+ - ๐Ÿ’ฌ `default_prompt` โ€“ Prompt for generation tasks
166
+ - ๐Ÿงพ Metadata:
167
+ - `dicom_id`, `study_id`, `subject_id`
168
+ - Acquisition info: `Rows`, `Columns`, `StudyDate`, `ViewPosition`, etc.
169
+
170
+ ---
171
+
172
+ ## ๐Ÿš€ How to Use
173
+
174
+ ```python
175
+ from datasets import load_dataset
176
+
177
+ # Load a specific subset (e.g., findings_section)
178
+ ds = load_dataset("X-iZhang/MIMIC-CXR-RRG", name="findings_section", split="test")
179
+
180
+ # Display an image
181
+ from PIL import Image
182
+ ds[0]["main_image"].show()
183
+
184
+ # View sample
185
+ print(ds[0]["findings_section"])
186
+ ```
187
+
188
+ ## โœ๏ธ Citation
189
+ ```
190
+ @misc{zhang2025libraleveragingtemporalimages,
191
+ title={Libra: Leveraging Temporal Images for Biomedical Radiology Analysis},
192
+ author={Xi Zhang and Zaiqiao Meng and Jake Lever and Edmond S. L. Ho},
193
+ year={2025},
194
+ eprint={2411.19378},
195
+ archivePrefix={arXiv},
196
+ primaryClass={cs.CV},
197
+ url={https://arxiv.org/abs/2411.19378},
198
+ }
199
+ ```