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cs.CV2025
Reducing Domain Gap with Diffusion-Based Domain Adaptation for Cell Counting
Mohammad Dehghanmanshadi, Wallapak Tavanapong
Generating realistic synthetic microscopy images is critical for training deep learning models in label-scarce environments, such as cell counting with many cells per image. Howeve…
cs.CV2025
CountXplain: Interpretable Cell Counting with Prototype-Based Density Map Estimation
Abdurahman Ali Mohammed, Wallapak Tavanapong, Catherine Fonder +1
Cell counting in biomedical imaging is pivotal for various clinical applications, yet the interpretability of deep learning models in this domain remains a significant challenge. W…
cs.CV2025
CellFMCount: A Fluorescence Microscopy Dataset, Benchmark, and Methods for Cell Counting
Abdurahman Ali Mohammed, Catherine Fonder, Ying Wei +4
Accurate cell counting is essential in various biomedical research and clinical applications, including cancer diagnosis, stem cell research, and immunology. Manual counting is lab…