# Position-Guided Prompt Learning for State-of-the-Art Anomaly Detection in Chest X-Rays

Jun 4, 2024

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GitHub’s PPAD: Leading Anomaly Detection in Chest X-Rays

GitHub introduces an innovative technique named PPAD, designed to enhance anomaly detection in chest X-ray imaging. This groundbreaking approach leverages position-guided prompts, enabling the model to concentrate on precise areas of interest within the images. By doing so, PPAD effectively reduces the disparity often found between the pre-training data and the specific data needed for accurate anomaly detection.

Additionally, the method incorporates a unique Structure-preserving Anomaly Synthesis during its training phase, further refining the system’s ability to identify abnormalities. Comparative studies demonstrate that PPAD surpasses previous methods across a variety of datasets. The details of this project, along with the complete code, are shared openly under the MIT License, promoting transparency and encouraging further research in this vital domain.