Project Description or Abstract Cancer is a highly heterogeneous disease, and the development of successful treatment strategies requires an understanding of the cellular mechanisms that result in diversity of cancer cell dynamics and interactions with the tissue environment. Quantitative imaging is a powerful tool for understanding these cellular mechanisms. New quantitative imaging methods, including light sheet microscopy, super-resolution microscopy and machine learning approaches to biological image analysis, have enabled previously impossible experiments. Proper training in the fundamental principles of quantitative imaging is essential to generating reliable data, correctly interpreting experiments, and enhancing the reproducibility of cancer research. The Cold Spring Harbor Laboratory proposes to continue the course “Quantitative Imaging: From Acquisition to Analysis”, to be held in the spring of 2021-2025. This two-week intensive course provides students with a thorough foundation in state-of-the-art quantitative light microscopy and image analysis techniques. The course is designed to engage a multidisciplinary audience, including biologists, physicists, engineers and computer scientists at all career stages, from graduate student to Principal Investigator. A unique aspect of this course is its strong emphasis on generating accurate and precise quantitative imaging data. A typical day of the course includes didactic lectures, a research seminar, a group discussion session and focused quantitative imaging laboratory exercises. The exercises include both image acquisition and analysis, and are planned such that, over the duration of the course, the most common types of quantitative measurements used in cancer research are covered, including: co-localization, measurement of fluorescence intensities, live specimen imaging,3D-image analysis, and detection/tracking/counting of diffraction-limited objects, subcellular structures, and whole cells. Students learn to use a wide range of imaging modalities to complete the exercises, including widefield fluorescence, point-scanning and spinning disk confocal, total internal reflection fluorescence, light sheet and super-resolution microscopy. A suite of computers equipped with free open-source software are used to process data and make measurements using modern image analysis methods, including machine learning approaches. In the daily group discussion, students present and discuss their results with the course instructors, thereby developing expertise in assessing the quality of quantitative measurements and critical troubleshooting skills. The instructors are internationally recognized leaders in quantitative microscopy and computational image analysis, and invited seminar speakers provide examples of expert use of quantitative imaging to answer biological questions. Quantitative Imaging: From Acquisition to Analysis provides training in quantitative microscopy that is crucial for advancing the m...