2 research outputs found
Automatic detection of lumen and media in the IVUS images using U-Net with VGG16 Encoder
Coronary heart disease is one of the top rank leading cause of mortality in
the world which can be because of plaque burden inside the arteries.
Intravascular Ultrasound (IVUS) has been recognized as power- ful imaging
technology which captures the real time and high resolution images of the
coronary arteries and can be used for the analysis of these plaques. The IVUS
segmentation involves the extraction of two arterial walls components namely,
lumen and media. In this paper, we investi- gate the effectiveness of
Convolutional Neural Networks including U-Net to segment ultrasound scans of
arteries. In particular, the proposed seg- mentation network was built based on
the the U-Net with the VGG16 encoder. Experiments were done for evaluating the
proposed segmen- tation architecture which show promising quantitative and
qualitative results.Comment: 10 pages, under review for International Conference of Smart
Multimedia (ICSM) 201
Analysis of Big Data Technology for Health Care Services
Deep learning and other big data technologies have over time become very
powerful and accurate. There are algorithms and models developed that have near
human accuracy in their task. In health care, the amount of data available is
massive and hence, these technologies have a great scope in health care. This
paper reviews a few interesting contributions to the field specifically to
medical imaging, genomics and patient health records.Comment: Accepted at the International Conference on Intelligent Technologies
and Applications(INTAP) 201