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Accurate detection of macro and microvesicles in rat models of fatty liver disease is crucial in evaluating the progression of liver disease and identifying potential hepatotoxic findings during drug development. In this paper, we present a deep-learning-based framework for the segmentation of vacuoles in liver images of Wistar rat and study the correlation of automated quantification with expert pathologist's manual evaluation. To address the issue of misclassification of lumina (vascular and bile duct) as large vacuoles, we propose a se
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