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name
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48
48
subject
int64
1
1
task
stringclasses
13 values
condition
stringclasses
1 value
bbox
listlengths
4
4
X
listlengths
1
6
Y
listlengths
1
6
T
listlengths
1
6
length
int64
1
6
fixOnTarget
bool
1 class
correct
int64
1
1
split
stringclasses
3 values
a3e1945f-24798491-79bf0265-7ae43733-d98951d4.jpg
1
lung opacity
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test
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pneumonia
present
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true
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test
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cardiomegaly
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train
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train
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test
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true
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valid
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support devices
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test
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cardiomegaly
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true
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valid
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cardiomegaly
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lung opacity
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true
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train
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train
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edema
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train
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valid
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lung opacity
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true
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valid
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1
cardiomegaly
present
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true
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train
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train
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train
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lung opacity
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test
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train
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train
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train
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train
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test
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test
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test
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train
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train
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train
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pleural effusion
present
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[ 113, 94, 35, 19, 12, 164 ]
[ 63, 91, 139, 154, 154, 131 ]
[ 0.38757, 0.3728, 0.27625, 0.45251, 0.7439, 0.51794 ]
6
true
1
test
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1
cardiomegaly
present
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[ 142, 109, 140, 133, 120, 137 ]
[ 85, 108, 99, 103, 94, 63 ]
[ 0.09546, 0.2583, 0.37231, 0.30664, 0.25879, 0.43701 ]
6
true
1
train
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1
atelectasis
present
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[ 188, 45, 192, 166, 186, 202 ]
[ 122, 126, 117, 108, 120, 131 ]
[ 0.40356, 0.24316, 0.55029, 0.08081, 0.35059, 0.19604 ]
6
true
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train
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atelectasis
present
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6
true
1
train
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1
cardiomegaly
present
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6
true
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train
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1
lung opacity
present
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[ 0.29102, 0.29077, 0.57568, 0.67163, 0.32349, 0.25806 ]
6
true
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train
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1
cardiomegaly
present
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[ 124, 125, 123, 126, 157, 155 ]
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6
true
1
train
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lung opacity
present
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6
true
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train
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1
edema
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[ 68, 73, 101, 165, 187, 168 ]
[ 139, 120, 114, 110, 145, 158 ]
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6
true
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train
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1
cardiomegaly
present
[ 0, 0, 0, 0 ]
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[ 0.29529, 0.29834, 0.1156, 0.11646, 0.34631 ]
5
true
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train
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1
support devices
present
[ 0, 0, 0, 0 ]
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[ 133, 138, 110, 114, 150, 140 ]
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6
true
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train
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atelectasis
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[ 0, 0, 0, 0 ]
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[ 133, 147, 150, 154, 157, 149 ]
[ 0.2312, 0.19788, 0.36255, 0.95667, 0.56055, 0.39587 ]
6
true
1
train
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1
pleural effusion
present
[ 0, 0, 0, 0 ]
[ 48, 119, 176, 33, 39, 57 ]
[ 133, 147, 150, 154, 157, 149 ]
[ 0.2312, 0.19788, 0.36255, 0.95667, 0.56055, 0.39587 ]
6
true
1
train
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1
cardiomegaly
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[ 78, 137, 155, 123, 90, 131 ]
[ 0.22668, 0.24216, 0.26297, 0.30725, 0.37134, 0.25861 ]
6
true
1
test
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1
atelectasis
present
[ 0, 0, 0, 0 ]
[ 45, 93, 170, 87, 51, 38 ]
[ 137, 106, 112, 79, 93, 104 ]
[ 0.40088, 0.26074, 0.43494, 0.24255, 0.59851, 0.54956 ]
6
true
1
train
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1
cardiomegaly
present
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[ 108, 132, 127 ]
[ 135, 112, 90 ]
[ 0.24261, 0.27518, 0.30869 ]
3
true
1
test
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1
support devices
present
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[ 135, 124, 112, 118, 94 ]
[ 0.24261, 0.72783, 0.29115, 0.31947, 0.29103 ]
5
true
1
train
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1
lung opacity
present
[ 0, 0, 0, 0 ]
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[ 88, 80, 134, 131, 135, 124 ]
[ 0.24513, 0.32248, 0.37392, 0.19624, 0.30609, 0.26149 ]
6
true
1
test
dd835ff3-23fd8ffe-98d639bf-b322a961-0dfdb1de.jpg
1
pneumonia
present
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[ 48, 43, 80, 59, 52, 131 ]
[ 85, 87, 84, 67, 86, 76 ]
[ 0.21045, 0.22607, 0.06641, 0.26831, 0.13501, 0.16187 ]
6
true
1
train
d5733e12-c8dcf091-45f17b61-2a47d8e7-27b815b6.jpg
1
enlarged cardiomediastinum
present
[ 0, 0, 0, 0 ]
[ 123, 105, 108, 134, 161, 156 ]
[ 42, 36, 77, 56, 67, 105 ]
[ 0.29663, 0.39697, 0.13147, 0.21362, 0.29675, 0.36255 ]
6
true
1
train
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1
edema
present
[ 0, 0, 0, 0 ]
[ 66, 168, 140, 71, 84, 107 ]
[ 96, 90, 97, 99, 104, 80 ]
[ 0.54407, 0.16516, 0.2804, 0.34644, 0.13147, 0.2467 ]
6
true
1
train
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1
lung opacity
present
[ 0, 0, 0, 0 ]
[ 38, 69, 50, 66, 50, 54 ]
[ 167, 123, 146, 129, 136, 142 ]
[ 0.32361, 0.67944, 0.56604, 0.57715, 0.53394, 0.38782 ]
6
true
1
train
8d805c57-4d2b05ce-6ea341d8-7b2edba5-c6addf2d.jpg
1
pleural effusion
present
[ 0, 0, 0, 0 ]
[ 38, 69, 50, 66, 50, 54 ]
[ 167, 123, 146, 129, 136, 142 ]
[ 0.32361, 0.67944, 0.56604, 0.57715, 0.53394, 0.38782 ]
6
true
1
train
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1
pneumonia
present
[ 0, 0, 0, 0 ]
[ 193, 129, 86, 62, 43, 89 ]
[ 142, 61, 89, 121, 170, 102 ]
[ 0.53406, 0.27173, 0.22632, 0.25903, 0.26025, 0.40442 ]
6
true
1
test
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1
support devices
present
[ 0, 0, 0, 0 ]
[ 107, 126, 127, 95, 103, 145 ]
[ 112, 87, 55, 80, 116, 143 ]
[ 0.56836, 0.21191, 0.24219, 0.20996, 0.80859, 0.59863 ]
6
true
1
train
3740d2e8-e76dc38e-398d0e7d-6c7c0f0a-37aee743.jpg
1
pleural effusion
present
[ 0, 0, 0, 0 ]
[ 114, 171, 81, 52, 99, 88 ]
[ 120, 127, 134, 107, 110, 79 ]
[ 0.20605, 0.5332, 0.13086, 0.29102, 0.19336, 0.22656 ]
6
true
1
train
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1
support devices
present
[ 0, 0, 0, 0 ]
[ 100, 123, 103, 117 ]
[ 36, 96, 102, 90 ]
[ 0.14926, 0.41977, 0.53857, 0.61453 ]
4
true
1
train
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1
lung lesion
present
[ 0, 0, 0, 0 ]
[ 124, 96, 95, 62, 44, 33 ]
[ 57, 81, 63, 109, 97, 119 ]
[ 0.74396, 0.30707, 0.29123, 0.40411, 0.30746, 2.66879 ]
6
true
1
train
73b633c5-0a010901-0d67b6a6-c0915884-eafeed0a.jpg
1
lung opacity
present
[ 0, 0, 0, 0 ]
[ 87, 87, 179, 172, 174, 172 ]
[ 115, 121, 114, 99, 95, 111 ]
[ 0.27405, 0.2413, 0.88895, 0.3396, 0.13068, 0.32068 ]
6
true
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train
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1
lung opacity
present
[ 0, 0, 0, 0 ]
[ 158, 92, 168, 81, 74, 85 ]
[ 89, 111, 109, 116, 131, 95 ]
[ 0.35229, 0.4043, 0.40454, 0.46875, 0.87231, 0.32007 ]
6
true
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train
3283bf63-a05bb530-3a600e92-b89d4466-e17f7876.jpg
1
pneumonia
present
[ 0, 0, 0, 0 ]
[ 158, 92, 168, 81, 74, 85 ]
[ 89, 111, 109, 116, 131, 95 ]
[ 0.35229, 0.4043, 0.40454, 0.46875, 0.87231, 0.32007 ]
6
true
1
train
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1
lung opacity
present
[ 0, 0, 0, 0 ]
[ 43, 59, 38, 38, 37, 49 ]
[ 110, 92, 124, 86, 97, 58 ]
[ 0.32343, 0.51736, 0.43616, 0.29117, 0.25922, 0.22522 ]
6
true
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train
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1
atelectasis
present
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[ 84, 94, 93, 126, 134, 133 ]
[ 0.2334, 0.53418, 0.56543, 0.37109, 0.24316, 0.32227 ]
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train
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1
cardiomegaly
present
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[ 151, 122, 73, 69, 72, 149 ]
[ 107, 159, 138, 114, 102, 165 ]
[ 0.20605, 0.30859, 0.37061, 0.2583, 0.48535, 1.1001 ]
6
true
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train
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1
cardiomegaly
present
[ 0, 0, 0, 0 ]
[ 94, 115, 120, 122, 145, 162 ]
[ 97, 84, 111, 133, 154, 137 ]
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true
1
train
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1
pleural effusion
present
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[ 87, 72, 65, 152, 46, 22 ]
[ 146, 141, 115, 95, 117, 179 ]
[ 0.29819, 0.26346, 0.52759, 0.28018, 0.62622, 1.28702 ]
6
true
1
valid
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1
atelectasis
present
[ 0, 0, 0, 0 ]
[ 96, 187, 201, 196, 158, 141 ]
[ 126, 117, 123, 117, 104, 79 ]
[ 0.23077, 0.47818, 0.49496, 0.49356, 1.03851, 0.44684 ]
6
true
1
train
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1
lung opacity
present
[ 0, 0, 0, 0 ]
[ 74, 69, 68, 95, 90, 60 ]
[ 125, 109, 122, 57, 73, 74 ]
[ 0.16455, 0.3042, 0.59912, 0.38916, 0.20996, 0.21045 ]
6
true
1
test
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GazeSearch: Radiology Findings Search Benchmark (WACV 2025)

Access is gated. This dataset contains images derived from MIMIC-CXR and is only shared with users credentialed under the PhysioNet Credentialed Health Data Use Agreement. Click Request access at the top of the page and confirm you hold an active MIMIC-CXR credentialed-access account; requests without proof of authorization will be denied.

GazeSearch is a curated visual search dataset for evaluating search algorithms on radiology findings. It is built from medical eye-tracking data (REFLACX and EGD) paired with chest X-ray images from MIMIC-CXR, and captures how radiologists visually search for specific findings.

Paper: GazeSearch: Radiology Findings Search Benchmark (WACV 2025). Original repository: https://github.com/uark-aicv/GazeSearch

Contents

gazesearch/
├── annotations/
│   └── finding_visual_search_coco_format_train_test_filtered_max_6_split_train_valid_test_2024-07-22.json
├── images/                      # 3,577 chest X-ray JPGs (from MIMIC-CXR)
└── checkpoints/
    ├── ckp_29999.pt             # ChestSearch model checkpoint (30k iterations)
    ├── M2F_R50.pkl              # Mask2Former ResNet-50 backbone weights
    └── M2F_R50_MSDeformAttnPixelDecoder.pkl  # MSD pixel decoder weights

Annotation format

The JSON file is a list of scanpath samples (4,875 entries over 2,328 unique images). Each entry has:

Field Description
name Image filename in images/
subject Radiologist / subject ID
task Target finding being searched (e.g. lung opacity, cardiomegaly, ...)
condition Presence of the finding (present)
bbox Ground-truth bounding box [x, y, w, h] of the finding
X, Y Fixation coordinates (in the 224×224 patch space)
T Fixation durations (seconds)
length Number of fixations (max 6; add a center fixation to get length-7 paper setup)
fixOnTarget Whether the scanpath ends on the target region
correct Whether the radiologist's decision was correct
split One of train (3,870) / valid (517) / test (488)

Tasks / findings

lung opacity, support devices, cardiomegaly, pleural effusion, atelectasis, edema, consolidation, enlarged cardiomediastinum, lung lesion, fracture, pneumonia, pneumothorax, pleural other.

Checkpoints

checkpoints/ckp_29999.pt is the trained ChestSearch scanpath-prediction baseline from the paper. M2F_R50.pkl and M2F_R50_MSDeformAttnPixelDecoder.pkl are the Mask2Former ResNet-50 backbone / pixel-decoder weights used to initialize training.

See the original repo for training/inference code and the src/demo_medical.ipynb demo notebook.

Citation

@article{GazeSearch2023,
    title={GazeSearch: Radiology Findings Search Benchmark},
    author={Trong Thang Pham and Tien-Phat Nguyen and Yuki Ikebe and Akash Awasthi and Zhigang Deng and Carol C. Wu and Hien Nguyen and Ngan Le},
    journal={IEEE Winter Conference on Applications of Computer Vision (WACV)},
    year={2025}
}

License

MIT License — Copyright (c) 2024 AICV@University of Arkansas. Note that the underlying MIMIC-CXR images are subject to the PhysioNet Credentialed Health Data License; only users credentialed for MIMIC-CXR should use this dataset.

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