@article{ART002277542},
author={신승연 and Hyunjin Kim and SANGHYUN PARK},
title={Recent Trend of Biomedical Image Classification Methods},
journal={Journal of Knowledge Information Technology and Systems},
issn={1975-7700},
year={2017},
volume={12},
number={5},
pages={765-776},
doi={10.34163/jkits.2017.12.5.016}
TY - JOUR
AU - 신승연
AU - Hyunjin Kim
AU - SANGHYUN PARK
TI - Recent Trend of Biomedical Image Classification Methods
JO - Journal of Knowledge Information Technology and Systems
PY - 2017
VL - 12
IS - 5
PB - Korea Knowledge Information Technology Society
SP - 765
EP - 776
SN - 1975-7700
AB - As biomedical imaging equipment and machine learning algorithms are improved, biomedical image analysis became a popular topic for both biologists and machine learning researchers. Biomedical image analysis includes various topics such as classification, segmentation, and registration. All of them are being actively studied, and there are a lot of remarkable papers on these topics. In this paper, we focus on recent trend of biomedical image classification. Because researchers use microscopy images for biological image analysis and use radiological data such as CT, MRI for medical image analysis, we explain classification methods used in several researches for biological image and medical image separately, depending on the type of images to be analyzed. In addition to traditional methods based on feature descriptor, we also introduce methods that apply deep learning in biomedical image classification, since deep learning is recently used in many researches for image processing. We found that deep learning based models show great performance in biomedical domain, and state-of-the-art idea of image processing and computer vision has potential to be applied to biomedical problems. Finally we suggest future works for better biomedical image classifier, based on the idea that are recently studied in computer vision, but with few papers in biomedical domain.
KW - Biomedical images;Image classification;Radiology;Computer vision;Machine learning
DO - 10.34163/jkits.2017.12.5.016
ER -
신승연, Hyunjin Kim and SANGHYUN PARK. (2017). Recent Trend of Biomedical Image Classification Methods. Journal of Knowledge Information Technology and Systems, 12(5), 765-776.
신승연, Hyunjin Kim and SANGHYUN PARK. 2017, "Recent Trend of Biomedical Image Classification Methods", Journal of Knowledge Information Technology and Systems, vol.12, no.5 pp.765-776. Available from: doi:10.34163/jkits.2017.12.5.016
신승연, Hyunjin Kim, SANGHYUN PARK "Recent Trend of Biomedical Image Classification Methods" Journal of Knowledge Information Technology and Systems 12.5 pp.765-776 (2017) : 765.
신승연, Hyunjin Kim, SANGHYUN PARK. Recent Trend of Biomedical Image Classification Methods. 2017; 12(5), 765-776. Available from: doi:10.34163/jkits.2017.12.5.016
신승연, Hyunjin Kim and SANGHYUN PARK. "Recent Trend of Biomedical Image Classification Methods" Journal of Knowledge Information Technology and Systems 12, no.5 (2017) : 765-776.doi: 10.34163/jkits.2017.12.5.016
신승연; Hyunjin Kim; SANGHYUN PARK. Recent Trend of Biomedical Image Classification Methods. Journal of Knowledge Information Technology and Systems, 12(5), 765-776. doi: 10.34163/jkits.2017.12.5.016
신승연; Hyunjin Kim; SANGHYUN PARK. Recent Trend of Biomedical Image Classification Methods. Journal of Knowledge Information Technology and Systems. 2017; 12(5) 765-776. doi: 10.34163/jkits.2017.12.5.016
신승연, Hyunjin Kim, SANGHYUN PARK. Recent Trend of Biomedical Image Classification Methods. 2017; 12(5), 765-776. Available from: doi:10.34163/jkits.2017.12.5.016
신승연, Hyunjin Kim and SANGHYUN PARK. "Recent Trend of Biomedical Image Classification Methods" Journal of Knowledge Information Technology and Systems 12, no.5 (2017) : 765-776.doi: 10.34163/jkits.2017.12.5.016
