H
Heng-Da Cheng
Researcher at Utah State University
Publications - 237
Citations - 11404
Heng-Da Cheng is an academic researcher from Utah State University. The author has contributed to research in topics: Image segmentation & Fuzzy logic. The author has an hindex of 49, co-authored 234 publications receiving 10214 citations. Previous affiliations of Heng-Da Cheng include Halifax & Harbin Institute of Technology.
Papers
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Proceedings ArticleDOI
Medical Knowledge Constrained Semantic Breast Ultrasound Image Segmentation
TL;DR: An effective approach using information extended images to train a fully convolutional network (FCN) to semantically segment BUS image into 3 categories: mammary layer, tumor, and background; and applying layer structure information to the conditional random field (CRF) for conducting breast cancer segmentation and making the segmentation result more accurate is proposed.
Journal ArticleDOI
Segmentation of ultrasound breast images based on a neutrosophic method
TL;DR: This paper employs neutrosophy and develops a fully automatic algorithm for BUS image segmentation that integrates two conflicting opinions about Speckle in ultrasound image: speckle is noise and speckel includes pattern information.
Proceedings ArticleDOI
A Fully Automatic Breast Ultrasound Image Segmentation Approach Based on Neutro-Connectedness
TL;DR: The newly proposed neutro-connectedness models the inherent uncertainty and indeterminacy of the spatial topological properties of the image and is more accurate and robust in segmenting tumors in BUS images.
Journal ArticleDOI
Image segmentation using fuzzy homogeneity criterion
TL;DR: This method will have wide application in image processing and take account of the spatial gray-tone dependence; thus, using homogeneity vectors has a better noise tolerance.