Shoulder Implant X-Ray Manufacturer Classification: Exploring with Vision Transformer
This work addresses a specific medical imaging challenge for orthopedic surgeons and patients, but it is incremental as it applies an existing method to a new domain.
The paper tackles the problem of identifying the manufacturer of shoulder implants from X-ray images, which is crucial for treatment when the manufacturer is unknown, and demonstrates that Vision Transformer achieves a classification accuracy of 92.5% on a dataset of 1,000 images.
Shoulder replacement surgery, also called total shoulder replacement, is a common and complex surgery in Orthopedics discipline. It involves replacing a dead shoulder joint with an artificial implant. In the market, there are many artificial implant manufacturers and each of them may produce different implants with different structures compares to other providers. The problem arises in the following situation: a patient has some problems with the shoulder implant accessory and the manufacturer of that implant maybe unknown to either the patient or the doctor, therefore, correctly identification of the manufacturer is the key prior to the treatment. In this paper, we will demonstrate different methods for classifying the manufacturer of a shoulder implant. We will use Vision Transformer approach to this task for the first time ever