With the development of digital technology, computers have been widely used in the medical field to improve operational efficiency. For example, the widespread use of electronic medical record systems has enabled general hospitals to share diagnostic information across departments and to check the history of past illnesses.
Until recently, radiographs taken on film were developed and read using a Shaukasten, but now radiographs are taken digitally and can be read on the spot using an LCD monitor. This project is based on image processing and machine learning technologies to detect and mark up lesion areas on radiographs, with the aim of reducing the burden on physicians in diagnostic imaging.
