image
listlengths 1
1
| conversations
listlengths 2
2
|
|---|---|
[
"/home/myid/yl80817/mimic-eye-integrating-mimic-datasets-with-reflacx-and-eye-gaze-for-multimodal-deep-learning-applications-1.0.0/mimic-eye/patient_19985757/CXR-JPG/s53940343/a8c685a6-4e2d1a2c-e84325b2-77abeba9-bd93898c.jpg"
] |
[
{
"from": "human",
"value": "<image>\nGiven the radiology report below, output the single bounding box of the most clinically relevant region as JSON with integer pixel coordinates [x1,y1,x2,y2] in the image pixel space.\n\nReport:\nN/A"
},
{
"from": "gpt",
"value": "{\"bbox\": [368, 341, 1268, 2319]}"
}
] |
[
"/home/myid/yl80817/mimic-eye-integrating-mimic-datasets-with-reflacx-and-eye-gaze-for-multimodal-deep-learning-applications-1.0.0/mimic-eye/patient_19985757/CXR-JPG/s53940343/a8c685a6-4e2d1a2c-e84325b2-77abeba9-bd93898c.jpg"
] |
[
{
"from": "human",
"value": "<image>\nGiven the radiology report below, output the single bounding box of the most clinically relevant region as JSON with integer pixel coordinates [x1,y1,x2,y2] in the image pixel space.\n\nReport:\nN/A"
},
{
"from": "gpt",
"value": "{\"bbox\": [491, 1036, 1241, 1500]}"
}
] |
[
"/home/myid/yl80817/mimic-eye-integrating-mimic-datasets-with-reflacx-and-eye-gaze-for-multimodal-deep-learning-applications-1.0.0/mimic-eye/patient_19985757/CXR-JPG/s53940343/a8c685a6-4e2d1a2c-e84325b2-77abeba9-bd93898c.jpg"
] |
[
{
"from": "human",
"value": "<image>\nGiven the radiology report below, output the single bounding box of the most clinically relevant region as JSON with integer pixel coordinates [x1,y1,x2,y2] in the image pixel space.\n\nReport:\nN/A"
},
{
"from": "gpt",
"value": "{\"bbox\": [559, 395, 1268, 1036]}"
}
] |
[
"/home/myid/yl80817/mimic-eye-integrating-mimic-datasets-with-reflacx-and-eye-gaze-for-multimodal-deep-learning-applications-1.0.0/mimic-eye/patient_19985757/CXR-JPG/s53940343/a8c685a6-4e2d1a2c-e84325b2-77abeba9-bd93898c.jpg"
] |
[
{
"from": "human",
"value": "<image>\nGiven the radiology report below, output the single bounding box of the most clinically relevant region as JSON with integer pixel coordinates [x1,y1,x2,y2] in the image pixel space.\n\nReport:\nN/A"
},
{
"from": "gpt",
"value": "{\"bbox\": [1077, 204, 1555, 1337]}"
}
] |
[
"/home/myid/yl80817/mimic-eye-integrating-mimic-datasets-with-reflacx-and-eye-gaze-for-multimodal-deep-learning-applications-1.0.0/mimic-eye/patient_19985757/CXR-JPG/s53940343/a8c685a6-4e2d1a2c-e84325b2-77abeba9-bd93898c.jpg"
] |
[
{
"from": "human",
"value": "<image>\nGiven the radiology report below, output the single bounding box of the most clinically relevant region as JSON with integer pixel coordinates [x1,y1,x2,y2] in the image pixel space.\n\nReport:\nN/A"
},
{
"from": "gpt",
"value": "{\"bbox\": [1105, 613, 1664, 1337]}"
}
] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.