We present a novel cell instance segmentation dataset named Revvity-25. It includes 110 high-resolution 1080 x 1080 brightfield images, each containing, on average, 27 manually labeled and expert-validated cancer cells, totaling 2937 annotated cells. To our knowledge, this is the first dataset with accurate and detailed annotations for cell borders and overlaps, with each cell annotated using an average of 60 polygon points, reaching up to 400 points for more complex structures. Revvity-25 dataset provides a unique resource that opens new possibilities for testing and benchmarking models for modal and amodal semantic and instance segmentation. Dataset is available here.