|
|
| |
 |
| |
| |
|
|
| |
|
| Faculty : |
School of Information, Computer, and Communication Technology (ICT) |
| Name : |
Dr. Bunyarit Uyyanonvara (Associate Professor) |
| Position : |
Associate Professor |
| E - Mail : |
bunyarit@siit.tu.ac.th |
| Phone Rangsit : |
|
| Phone Bangkadi : |
+66 (0) 2501 3505-20 |
| Phone Extension : |
2005 |
|
|
| |
|
|
|
- B.Sc. (1st Class Honors) in Science (Physics), Prince of Songkhla University, Thailand
- Ph.D. in Image Processing, King's College, University of London, UK
|
|
|
|
- 2007 Best Teaching Award, Sirindhorn International Institute of Technology.
- 2003 Best Teaching Award, Sirindhorn International Institute of Technology.
- Development and Promotion of Science and Technology Talents Project (DPST) Scholarship, 1990-2000.
|
|
|
|
Medical image processing, Pattern recognition. |
|
|
|
Image Segmentation Using Texture and Relaxation Labeling
Algorithms
When normal density or intensity segmentation is not effective enough, a new
representation of texture which is derived from the spatial energy of the
texture is introduced in order to segment the given image. From the energy
values, a 2D histogram of texture is generated. The texture histogram is used to
discriminate textures and to retrieve image segmentation. In an attempt to
assess the similarities in the regional areas, the property of adjacency could
be useful. This characteristic of pixels is defined as a co-occurrence matrix,
which is an important tool in Image Segmentation using Texture and Relaxation
Labeling Algorithms.
Medical Image Processing
Taking advantage of the high capability of computers, offering advantages
over film based systems, several image processing techniques are of interest,
especially for medical purposes in order to get most of the information out of
the given medical images. Essentially, medical imaging can make use of texture
information, texture feature classification or texture segmentation because of
the nature of the medical image itself. Medical assessment can then be made
fully automated later on and this will lead to a reduction of human errors,
increasing of consistency and repeatability. This can be distributed to the
remote areas or hospitals that lack sophisticated treatment facilities or
trained experts.
|
|
|
|
|
Master Theses Supervised |
|
| 2005: |
Kaittisin Kanjanawanishkul. Fast Adaptive Algorithm for Time-Critical Color Quantization Application. |
| 2007: |
Nyan Bo Bo. Robust Hand Tracking in Low-Resolution Video Sequences. |
| 2007: |
Viranee Thongnuch. Optic Disk Detection in Retinopathy of Prematurity. |
| Current: |
Uttapong Ruangrit. Consolidation of Heterogeneous Genome Database Systems. |
| Current: |
Thanakorn Suma. Projection Modification for Metal Artifacts Reduction in CT Using General Interpolation Methods.
|
|
Doctoral Theses Supervised |
|
| 2007: |
Lassada Sukkaew. Image Analysis for Automatic Dectection of Retinopathy of Prematurity. |
| Current: |
Akara Sopharak. Automatic Detection of Diabetic Retinopathy from Digital Retinal Images. |
| Current: |
Cattleya Duanggate. Scale Space on Exudates Detection. | |
|
| |
|
|
- 2002-Present: SIIT
- 2000 - 2002: Lecturer, Walailak University, Thailand.
- 2001 - 2002: Programme Coordinator, Management of Information Technology, Master Programme, Walailak University, Thailand.
- 1999 - 2000: Demonstrator in Physics Laboratory, King’s College, London, UK.
|
|
|
|
|
|
| |
| |
|
|
|
|
|
|
|