Could We Generate Cytology Images from Histopathology Images? An Empirical Study

arXiv:2403.10885v1 Announce Type: cross
Abstract: Automation in medical imaging is quite challenging due to the unavailability of annotated datasets and the scarcity of domain experts. In recent years, deep learning techniques have solved some complex medical imaging tasks like disease classification, important object localization, segmentation, etc. However, most of the task requires a large amount of annotated data for their successful implementation. To mitigate the shortage of data, different generative models are proposed for data augmentation purposes which can boost …

abstract arxiv automation classification cs.cv datasets deep learning deep learning techniques disease domain domain experts eess.iv etc experts generate however images imaging localization medical medical imaging object segmentation study tasks type