If every breath is strained and painful, it could be a serious and potentially life-threatening condition. A pulmonary embolism (PE) is caused by an artery blockage in the lung. It is time consuming to confirm a PE and prone to overdiagnosis. Machine learning could help to more accurately identify PE cases, which would make management and treatment more effective for patients.
Currently, CT pulmonary angiography (CTPA), is the most common type of medical imaging to evaluate patients with suspected PE. These CT scans consist of hundreds of images that require detailed review to identify clots within the pulmonary arteries. As the use of imaging continues to grow, constraints of radiologists’ time may contribute to delayed diagnosis. The Radiological Society of North America (RSNA®) has teamed up with the Society of Thoracic Radiology (STR) to help improve the use of machine learning in the diagnosis of PE.
In this competition, you’ll detect and classify PE cases. In particular, you'll use chest CTPA images (grouped together as studies) and your data science skills to enable more accurate identification of PE. If successful, you'll help reduce human delays and errors in detection and treatment.With 60,000-100,000 PE deaths annually in the United States, it is among the most fatal cardiovascular diseases. Timely and accurate diagnosis will help these patients receive better care and may also improve outcomes.
The Radiological Society of North America (RSNA®) is an international society of radiologists, medical physicists, and other medical professionals with more than 53,400 members worldwide. RSNA hosts the world’s premier radiology forum and publishes two top peer-reviewed journals: Radiology, the highest-impact scientific journal in the field, and RadioGraphics, the only journal dedicated to continuing education in radiology. The Society of Thoracic Radiology (STR) was founded in 1982. The STR is dedicated to advancing cardiothoracic imaging in clinical application, education, and research in radiology and allied disciplines. Continuing professional development opportunities provided by the STR include educational and scientific meetings, mentorship programs, grant support and award opportunities, our society journal, Journal of Thoracic Imaging, and global collaboration activities.
| Sl. No. | Notebook Name | Kaggle Live Link |
|---|---|---|
| 1. | CNN-GRU Baseline- Stage2 Train+Inference | Kaggle Live Link |
| 2. | CT-Scans, DICOM files, Windowing Explained ✔️✔️ | Kaggle Live Link |
| 3. | RSNA-STR [✔️3D Stacking ✔️3D Plot ✔️Segmentation] | Kaggle Live Link |
| 4. | Pulmonary Fibrosis Progression [EDA, Lung Segment] | Kaggle Live Link |
| 5. | RSNA-STR-PE [Gradient & Sigmoid Windowing] | Kaggle Live Link |
| 6. | RSNA-STR Pulmonary Embolism [EDA + Domain Info] | Kaggle Live Link |
| 7. | RSNA-STR [DICOM ➭ GIF ➭ JPEG ➭ .npy] | Kaggle Live Link |
| 8. | Visualizing and Analyzing DICOMs in Python | Kaggle Live Link |
288th out of 784 teams (Top 37%) Leaderboard Link