Biological and medical applications generate an enormous number of high-resolution images, annotated extensively for many different purposes. The ability to interpret these images automatically enables Quantacell to answer new research questions more rapidly and ensure reproducibility.
Using MATLAB®, Quantacell has developed image analysis, machine learning, and deep learning prototypes for various applications. For example, they trained a deep learning model to help pathologists analyze kidney function from biopsy samples, achieving better results than visual inspection alone. They also used MATLAB to develop a complete algorithm combining deep learning and machine learning techniques in 24 hours, contributing to Quantacell winning a skin cancer–themed hackathon.
- A flexible environment that is easy to use for rapid prototyping
- A unified tool for the entire workflow, from annotation and visualization to algorithm development
- Built-in machine learning and deep learning algorithms