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Nipon Theera-Umpon
Researcher at Chiang Mai University
Publications - 150
Citations - 1802
Nipon Theera-Umpon is an academic researcher from Chiang Mai University. The author has contributed to research in topics: Support vector machine & Cluster analysis. The author has an hindex of 17, co-authored 140 publications receiving 1458 citations. Previous affiliations of Nipon Theera-Umpon include University of Missouri.
Papers
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Journal ArticleDOI
Automatic cervical cell segmentation and classification in Pap smears
TL;DR: The results show that the proposed automatic approach for automatic cervical cancer cell segmentation and classification yields very good performance and is better than its counterparts.
Journal ArticleDOI
Morphological Granulometric Features of Nucleus in Automatic Bone Marrow White Blood Cell Classification
Nipon Theera-Umpon,S. Dhompongsa +1 more
TL;DR: This paper investigates whether information about the nucleus alone is adequate to classify white blood cells, and shows that the features using nucleus alone can be utilized to achieve a classification rate of 77% on the test sets.
Book ChapterDOI
White blood cell segmentation and classification in microscopic bone marrow images
TL;DR: Even though the boundaries between cell classes are not well-defined and there are classification variations among experts, a promising classification performance is achieved using neural networks with five-fold cross validation.
Journal ArticleDOI
Boundary Detection in Medical Images Using Edge Following Algorithm Based on Intensity Gradient and Texture Gradient Features
TL;DR: The proposed segmentation technique is robust and applicable on various kinds of noisy images without prior knowledge of noise properties and yields better performance than the classical contour models.
Patch-Based White Blood Cell Nucleus Segmentation Using Fuzzy Clustering
TL;DR: A technique to segment singlecell images of white blood cells in bone marrow into two regions, i.e., nucleus and non-nucleus is proposed, based on the fuzzy C-means clustering and mathematical morphology.