4 papers
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…
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…
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…
IDCIA: Immunocytochemistry Dataset for Cellular Image Analysis
Abdurahman Ali Mohammed, Catherine Fonder, Donald S. Sakaguchi +3
We present a new annotated microscopic cellular image dataset to improve the effectiveness of machine learning methods for cellular image analysis. Cell counting is an important st…