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Xiangrong Zhou

Researcher at Gifu University

Publications -  123
Citations -  2780

Xiangrong Zhou is an academic researcher from Gifu University. The author has contributed to research in topics: Segmentation & Image segmentation. The author has an hindex of 23, co-authored 120 publications receiving 2362 citations.

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Volumetric quantitative analysis of tissue characteristics of coronary plaques after statin therapy using three-dimensional integrated backscatter intravascular ultrasound.

TL;DR: In this article, the authors evaluated the usefulness of 3D integrated backscatter (IB) intravascular ultrasound (IVUS) for quantitative tissue characterization of coronary plaques and used this imaging technique to determine if six months of statin therapy alters the tissue characteristics of coronary plaque.
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Age-related changes in trabecular and cortical bone microstructure.

TL;DR: The present paper addresses recently studied age-related changes in trabecular and cortical bone microstructure based primarily on HR-pQCT and micro-CT and focuses on the three-dimensional microst structure of the vertebrae, femoral neck, and distal radius, which are common osteoporotic fracture sites.
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An application of cascaded 3D fully convolutional networks for medical image segmentation.

TL;DR: This work shows that a multi-class 3D FCN trained on manually labeled CT scans of several anatomical structures can achieve competitive segmentation results, while avoiding the need for handcrafting features or training class-specific models.
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Assessment of Vulnerable Plaques Causing Acute Coronary Syndrome Using Integrated Backscatter Intravascular Ultrasound

TL;DR: Tissue characteristics of VP before ACS were different from those of SP, which suggests that VP and SP as classified by IB-IVUS are useful in predicting ACS.
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An application of cascaded 3D fully convolutional networks for medical image segmentation

TL;DR: In this paper, a coarse-to-fine 3D FCN is used to roughly define a candidate region, which is then used as input to a second FCN for more detailed segmentation of organs and vessels.