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Debabrata Ghosh
Researcher at University of Texas at Dallas
Publications - 14
Citations - 478
Debabrata Ghosh is an academic researcher from University of Texas at Dallas. The author has contributed to research in topics: Image resolution & Image stitching. The author has an hindex of 10, co-authored 14 publications receiving 359 citations. Previous affiliations of Debabrata Ghosh include Thapar University & University of North Dakota.
Papers
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Journal ArticleDOI
A survey on image mosaicing techniques
Debabrata Ghosh,Naima Kaabouch +1 more
TL;DR: An in-depth survey of the existing image mosaicing algorithms by classifying them into several groups, and the fundamental concepts are first explained and then the modifications made to the basic concepts by different researchers are explained.
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Hyposialylated IgG activates endothelial IgG receptor FcγRIIB to promote obesity-induced insulin resistance
Keiji Tanigaki,Anastasia Sacharidou,Jun Peng,Ken L. Chambliss,Ivan S. Yuhanna,Debabrata Ghosh,Debabrata Ghosh,Mohamed M. Ahmed,Alexander J. Szalai,Wanpen Vongpatanasin,Robert F. Mattrey,Qiushi Chen,Parastoo Azadi,Ildiko Lingvay,Marina Botto,William L. Holland,Jennifer J. Kohler,Shashank R. Sirsi,Kenneth Hoyt,Philip W. Shaul,Chieko Mineo +20 more
TL;DR: It is shown that activation of the IgG receptor Fc&ggr;RIIB in endothelium by hyposialylated IgG plays an important role in obesity-induced insulin resistance.
Journal ArticleDOI
Super-Resolution Ultrasound Imaging of Skeletal Muscle Microvascular Dysfunction in an Animal Model of Type 2 Diabetes.
Debabrata Ghosh,Debabrata Ghosh,Jun Peng,Katherine G. Brown,Shashank R. Sirsi,Shashank R. Sirsi,Chieko Mineo,Philip W. Shaul,Kenneth Hoyt,Kenneth Hoyt +9 more
TL;DR: To evaluate the use of super‐resolution ultrasound (SR‐US) imaging for quantifying microvascular changes in skeletal muscle using a mouse model of type 2 diabetes, super-resolution ultrasound is used in this study for the first time.
Journal ArticleDOI
Toward optimization of in vivo super-resolution ultrasound imaging using size-selected microbubble contrast agents
Debabrata Ghosh,Debabrata Ghosh,Fangyuan Xiong,Fangyuan Xiong,Shashank R. Sirsi,Shashank R. Sirsi,Philip W. Shaul,Robert F. Mattrey,Kenneth Hoyt,Kenneth Hoyt +9 more
TL;DR: This study indicates that MB size and dose and US system imaging rate and data acquisition length have significant impact on the quality of in vivo SR‐US images of skeletal muscle microvascularity.
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Deep Learning of Spatiotemporal Filtering for Fast Super-Resolution Ultrasound Imaging
TL;DR: The goal of this study was to evaluate the effectiveness of deep learning to realize a spatiotemporal filter in the context of SR-US processing and the performance of the 3DCNN was encouraging for real-time SR- US imaging.