Review on approaches to concept detection in medical images

Abstract

Concept detection in medical images involves the identification of various biomedical semantic entities in the images. This is a non-trivial task due to the highly heterogeneous nature of medical images. This heterogeneity is caused due to the different body parts, presence of abnormalities, and imaging techniques used to capture the image. In this paper, a thorough survey on important approaches to concept detection in medical images is presented. Methods such as multi-label classification, sequence-to-sequence learning, detecting concepts from captions, and similarity search-based approaches to concept detection in medical images are reviewed. This paper also highlights the challenges associated with the medical image concept detection task. Possible avenues for further research are also discussed.