Over the past few decades, medical imaging techniques, such as chest X-rays, computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET), mammography, and ultrasound, and have been used for the early detection, diagnosis, prognosis, and treatment of diseases. Various medical imaging analysis problems, such as medical image registration, detection of anatomical and cellular structures, tissue segmentation, have achieved state-of-the-art performances by applying computer vision techniques. However, how to securely and reliably deploy these technologies for facilitating further disease diagnosis and treatment planning remains an open question.

In this workshop, we aim to bring together researchers in computer vision, machine learning, healthcare, medicine, and clinical fields to facilitate discussions including related challenges, possible solutions and future directions. We hope that the proposed workshop is fruitful in offering a step toward building autonomous clinical decision systems with a higher-level understanding of medical computer vision.