The Image Analysis Collaboratory focuses on advancing the quantitative analysis of biomedical images, addressing challenges in image restoration, object detection, segmentation, co-localization analysis, tracking, and classification. Our mission encompasses both the application and development of cutting-edge methods in classical bioimage analysis, deep learning, and spatial statistics. These efforts are carried out in-house and through collaborations with a global network of experts.
We serve as a hub for bioimage analysis methodologies, bridging the gap between image-data owners and image-analysis practitioners. Our interdisciplinary team comprises physicists, mathematicians, computer scientists, engineers, and life scientists, all united by a shared passion for developing robust algorithms to extract meaningful insights from complex image data efficiently. Additionally, we are committed to fostering a culture of learning by teaching best practices and equipping the next generation of researchers with the tools to push the boundaries of biomedical imaging science.
Through our collaborative ethos and algorithmic expertise, we aim to elevate the role of quantitative image analysis in driving scientific discovery and innovation.