A Comprehensive Survey on Medical Image Blob Detection and Classification Models
Sitanaboina S L Parvathi, Harikiran Jonnadula · 2021 International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA) · 2021
In Health Care, the medical image processing becomes a necessary marathon for the Computer Aided Diagnostic (CAD) systems. Blobs are the heterogeneous small parts of an image, which helps in finding and locating the abnormalities and damages of the body organs from the digital medical images. For the disease early diagnosis and staging purpose, the blobs’ location, size, shape, center and radius like properties should be calculated from the medical images. As on, many former researchers were proposed several blob detections models and algorithms to accurately find the blobs from the medical images. Although many researchers proposed various blob detection models, they are still facing several limitations in detection, due to the indistinct boundaries and the diversity in shape and distribution of the blobs. As part of the research on blob detection, in this survey paper we are presenting the essential information regarding the medical image blob detection and classification models.