Medical Image Enhancement For Lesion Detection Based On Class-Aware Attention And Deep Colorization

摘要

The lesion detection on medical images has been a challenging problem in computer vision due to the lack of high-quality annotations at the bounding box level and the difficulty to identify the lesion on gray-scale medical images which are commonly used in radiology tests like X-ray, CT and MRI. In this paper, we propose a novel framework of medical image enhancement based on the class-aware attention weight extraction and the deep colorization of medical images with generative adversarial networks motivated by human visual characteristics and cell staining. The evaluation conducted on the real public medical image datasets proves that, the performance of lesion detection based on the existing detectors is improved after enhancing the medical images with the proposed enhancement framework.