PE-Positive Digital Subtraction CTPA with Annotations

This dataset is for pulmonary embolism diagnosis using non-contrast CT and CTPA. We provide high-quality, pixel-level annotations for emboli masks on both CTPA and non-contrast CT (registered from CTPA). Data Format All files are in numpy.float16 format, with a shape of [512, 512, 512]. Resolution: [334/512 mm, 334/512 mm, 1 mm] DICOM attribute: Image Orientation (Patient): [1, 0, 0, 0, 1, 0] Segmentation Format: Binary masks CT Intensity Scaling: CT_data * 1600 - 600 restores the original Hounsfield Unit (HU) values We also provide pulmonary artery-vein segmentations and emboli segmentations for the RSNA-PE Dataset. For the RSNA-PE Dataset, first convert DICOM to rescaled_CTPA using: 🔗 get_rescaled_ct.pyThen, normalize its Patient Orientation using: 🔗 normalize_direction.py Dataset Structure 📂 CT-CTPA-Paired_Dataset (200 cases)├── 📁 CTPA_Data│ ├── 📁 rescaled_CTPA│ ├── 📁 semantics│ ├── 📁 emboli_mask│ ├── 📁 airway_mask│ ├── 📁 artery_mask│ ├── 📁 vein_mask│ ├── 📁 blood_center_line│ ├── 📁 blood_branch_map ├── 📁 Non-Contrast_Data│ ├── 📁 rescaled_ct│ ├── 📁 semantics│ ├── 📁 emboli_mask│ ├── 📁 blood_vessel_lumen_mask│ ├── 📁 airway_mask│ ├── 📁 artery_mask│ ├── 📁 vein_mask│ ├── 📁 blood_center_line│ ├── 📁 blood_branch_map 📂 AV-Emboli_Seg_RSNA-PE-Dataset (7,222 cases)├── 📁 artery_mask├── 📁 emboli_mask├── 📁 vein_mask